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# Amazon Comprehend Medical contoh menggunakan AWS CLI
Contoh kode berikut menunjukkan cara melakukan tindakan dan menerapkan skenario umum AWS Command Line Interface dengan menggunakan Amazon Comprehend Medical.
*Tindakan* merupakan kutipan kode dari program yang lebih besar dan harus dijalankan dalam konteks. Sementara tindakan menunjukkan cara memanggil fungsi layanan individual, Anda dapat melihat tindakan dalam konteks dalam skenario terkait.
Setiap contoh menyertakan tautan ke kode sumber lengkap, di mana Anda dapat menemukan instruksi tentang cara mengatur dan menjalankan kode dalam konteks.
**Topics**
+ [Tindakan](#actions)
## Tindakan
### `describe-entities-detection-v2-job`
Contoh kode berikut menunjukkan cara menggunakan`describe-entities-detection-v2-job`.
**AWS CLI**
**Untuk menggambarkan pekerjaan deteksi entitas**
`describe-entities-detection-v2-job`Contoh berikut menampilkan properti yang terkait dengan pekerjaan deteksi entitas asinkron.
```
aws comprehendmedical describe-entities-detection-v2-job \
--job-id "ab9887877365fe70299089371c043b96"
```
Output:
```
{
"ComprehendMedicalAsyncJobProperties": {
"JobId": "ab9887877365fe70299089371c043b96",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-03-18T21:20:15.614000+00:00",
"EndTime": "2020-03-18T21:27:07.350000+00:00",
"ExpirationTime": "2020-07-16T21:20:15+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": ""
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "867139942017-EntitiesDetection-ab9887877365fe70299089371c043b96/"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "DetectEntitiesModelV20190930"
}
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [DescribeEntitiesDetectionV2Job](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/describe-entities-detection-v2-job.html) di Referensi *AWS CLI Perintah*.
### `describe-icd10-cm-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`describe-icd10-cm-inference-job`.
**AWS CLI**
**Untuk menggambarkan pekerjaan inferensi ICD-10-CM**
`describe-icd10-cm-inference-job`Contoh berikut menjelaskan properti pekerjaan inferensi yang diminta dengan job-id yang ditentukan.
```
aws comprehendmedical describe-icd10-cm-inference-job \
--job-id "5780034166536cdb52ffa3295a1b00a7"
```
Output:
```
{
"ComprehendMedicalAsyncJobProperties": {
"JobId": "5780034166536cdb52ffa3295a1b00a7",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-05-18T21:20:15.614000+00:00",
"EndTime": "2020-05-18T21:27:07.350000+00:00",
"ExpirationTime": "2020-09-16T21:20:15+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "0.1.0"
}
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [DescribeIcd10 CmInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/describe-icd10-cm-inference-job.html) di *Referensi AWS CLI Perintah*.
### `describe-phi-detection-job`
Contoh kode berikut menunjukkan cara menggunakan`describe-phi-detection-job`.
**AWS CLI**
**Untuk menggambarkan pekerjaan deteksi PHI**
`describe-phi-detection-job`Contoh berikut menampilkan properti yang terkait dengan pekerjaan deteksi informasi kesehatan yang dilindungi asinkron (PHI).
```
aws comprehendmedical describe-phi-detection-job \
--job-id "4750034166536cdb52ffa3295a1b00a3"
```
Output:
```
{
"ComprehendMedicalAsyncJobProperties": {
"JobId": "4750034166536cdb52ffa3295a1b00a3",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-03-19T20:38:37.594000+00:00",
"EndTime": "2020-03-19T20:45:07.894000+00:00",
"ExpirationTime": "2020-07-17T20:38:37+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": ""
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "867139942017-PHIDetection-4750034166536cdb52ffa3295a1b00a3/"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "PHIModelV20190903"
}
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [DescribePhiDetectionJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/describe-phi-detection-job.html)di *Referensi AWS CLI Perintah*.
### `describe-rx-norm-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`describe-rx-norm-inference-job`.
**AWS CLI**
**Untuk menggambarkan pekerjaan RxNorm inferensi**
`describe-rx-norm-inference-job`Contoh berikut menjelaskan properti pekerjaan inferensi yang diminta dengan job-id yang ditentukan.
```
aws comprehendmedical describe-rx-norm-inference-job \
--job-id "eg8199877365fc70299089371c043b96"
```
Output:
```
{
"ComprehendMedicalAsyncJobProperties": {
"JobId": "g8199877365fc70299089371c043b96",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-05-18T21:20:15.614000+00:00",
"EndTime": "2020-05-18T21:27:07.350000+00:00",
"ExpirationTime": "2020-09-16T21:20:15+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "0.0.0"
}
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [DescribeRxNormInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/describe-rx-norm-inference-job.html)di *Referensi AWS CLI Perintah*.
### `describe-snomedct-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`describe-snomedct-inference-job`.
**AWS CLI**
**Untuk menggambarkan pekerjaan inferensi CT SNOMED**
`describe-snomedct-inference-job`Contoh berikut menjelaskan properti pekerjaan inferensi yang diminta dengan job-id yang ditentukan.
```
aws comprehendmedical describe-snomedct-inference-job \
--job-id "2630034166536cdb52ffa3295a1b00a7"
```
Output:
```
{
"ComprehendMedicalAsyncJobProperties": {
"JobId": "2630034166536cdb52ffa3295a1b00a7",
"JobStatus": "COMPLETED",
"SubmitTime": "2021-12-18T21:20:15.614000+00:00",
"EndTime": "2021-12-18T21:27:07.350000+00:00",
"ExpirationTime": "2022-05-16T21:20:15+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "0.1.0"
}
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [DescribeSnomedctInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/describe-snomedct-inference-job.html)di *Referensi AWS CLI Perintah*.
### `detect-entities-v2`
Contoh kode berikut menunjukkan cara menggunakan`detect-entities-v2`.
**AWS CLI**
**Contoh 1: Untuk mendeteksi entitas langsung dari teks**
`detect-entities-v2`Contoh berikut menunjukkan entitas yang terdeteksi dan memberi label sesuai dengan jenis, langsung dari teks masukan.
```
aws comprehendmedical detect-entities-v2 \
--text "Sleeping trouble on present dosage of Clonidine. Severe rash on face and leg, slightly itchy."
```
Output:
```
{
"Id": 0,
"BeginOffset": 38,
"EndOffset": 47,
"Score": 0.9942955374717712,
"Text": "Clonidine",
"Category": "MEDICATION",
"Type": "GENERIC_NAME",
"Traits": []
}
```
Untuk informasi selengkapnya, lihat [Mendeteksi Entitas Versi 2](https://docs.aws.amazon.com/comprehend/latest/dg/extracted-med-info-V2.html) di Panduan Pengembang *Medis Amazon Comprehend*.
**Contoh 2: Untuk mendeteksi entitas dari jalur file**
`detect-entities-v2`Contoh berikut menunjukkan entitas yang terdeteksi dan memberi label sesuai dengan jenis dari jalur file.
```
aws comprehendmedical detect-entities-v2 \
--text file://medical_entities.txt
```
Isi dari `medical_entities.txt`:
```
{
"Sleeping trouble on present dosage of Clonidine. Severe rash on face and leg, slightly itchy."
}
```
Output:
```
{
"Id": 0,
"BeginOffset": 38,
"EndOffset": 47,
"Score": 0.9942955374717712,
"Text": "Clonidine",
"Category": "MEDICATION",
"Type": "GENERIC_NAME",
"Traits": []
}
```
Untuk informasi selengkapnya, lihat [Mendeteksi Entitas Versi 2](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-entitiesv2.html) di Panduan Pengembang *Medis Amazon Comprehend*.
+ Untuk detail API, lihat [DetectEntitiesV2](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/detect-entities-v2.html) di *Referensi AWS CLI Perintah*.
### `detect-phi`
Contoh kode berikut menunjukkan cara menggunakan`detect-phi`.
**AWS CLI**
**Contoh 1: Untuk mendeteksi informasi kesehatan yang dilindungi (PHI) langsung dari teks**
`detect-phi`Contoh berikut menampilkan entitas informasi kesehatan terlindungi (PHI) yang terdeteksi langsung dari teks masukan.
```
aws comprehendmedical detect-phi \
--text "Patient Carlos Salazar presented with rash on his upper extremities and dry cough. He lives at 100 Main Street, Anytown, USA where he works from his home as a carpenter."
```
Output:
```
{
"Entities": [
{
"Id": 0,
"BeginOffset": 8,
"EndOffset": 21,
"Score": 0.9914507269859314,
"Text": "Carlos Salazar",
"Category": "PROTECTED_HEALTH_INFORMATION",
"Type": "NAME",
"Traits": []
},
{
"Id": 1,
"BeginOffset": 94,
"EndOffset": 109,
"Score": 0.871849775314331,
"Text": "100 Main Street, Anytown, USA",
"Category": "PROTECTED_HEALTH_INFORMATION",
"Type": "ADDRESS",
"Traits": []
},
{
"Id": 2,
"BeginOffset": 145,
"EndOffset": 154,
"Score": 0.8302185535430908,
"Text": "carpenter",
"Category": "PROTECTED_HEALTH_INFORMATION",
"Type": "PROFESSION",
"Traits": []
}
],
"ModelVersion": "0.0.0"
}
```
Untuk informasi selengkapnya, lihat [Deteksi PHI](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-phi.html) di *Amazon Comprehend Medical Developer Guide*.
**Contoh 2: Untuk mendeteksi melindungi informasi kesehatan (PHI) langsung dari jalur file**
`detect-phi`Contoh berikut menunjukkan entitas informasi kesehatan terlindungi (PHI) yang terdeteksi dari jalur file.
```
aws comprehendmedical detect-phi \
--text file://phi.txt
```
Isi dari `phi.txt`:
```
"Patient Carlos Salazar presented with a rash on his upper extremities and a dry cough. He lives at 100 Main Street, Anytown, USA, where he works from his home as a carpenter."
```
Output:
```
{
"Entities": [
{
"Id": 0,
"BeginOffset": 8,
"EndOffset": 21,
"Score": 0.9914507269859314,
"Text": "Carlos Salazar",
"Category": "PROTECTED_HEALTH_INFORMATION",
"Type": "NAME",
"Traits": []
},
{
"Id": 1,
"BeginOffset": 94,
"EndOffset": 109,
"Score": 0.871849775314331,
"Text": "100 Main Street, Anytown, USA",
"Category": "PROTECTED_HEALTH_INFORMATION",
"Type": "ADDRESS",
"Traits": []
},
{
"Id": 2,
"BeginOffset": 145,
"EndOffset": 154,
"Score": 0.8302185535430908,
"Text": "carpenter",
"Category": "PROTECTED_HEALTH_INFORMATION",
"Type": "PROFESSION",
"Traits": []
}
],
"ModelVersion": "0.0.0"
}
```
Untuk informasi selengkapnya, lihat [Deteksi PHI](https://docs.aws.amazon.com/comprehend/latest/dg/how-medical-phi.html) di *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [DetectPhi](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/detect-phi.html)di *Referensi AWS CLI Perintah*.
### `infer-icd10-cm`
Contoh kode berikut menunjukkan cara menggunakan`infer-icd10-cm`.
**AWS CLI**
**Contoh 1: Untuk mendeteksi entitas kondisi medis dan menautkan ke Ontologi ICD-10-CM langsung dari teks**
`infer-icd10-cm`Contoh berikut memberi label pada entitas kondisi medis yang terdeteksi dan menghubungkan entitas tersebut dengan kode dalam edisi 2019 dari International Classification of Diseases Clinical Modification (ICD-10-CM).
```
aws comprehendmedical infer-icd10-cm \
--text "The patient complains of abdominal pain, has a long-standing history of diabetes treated with Micronase daily."
```
Output:
```
{
"Entities": [
{
"Id": 0,
"Text": "abdominal pain",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Score": 0.9475538730621338,
"BeginOffset": 28,
"EndOffset": 42,
"Attributes": [],
"Traits": [
{
"Name": "SYMPTOM",
"Score": 0.6724207401275635
}
],
"ICD10CMConcepts": [
{
"Description": "Unspecified abdominal pain",
"Code": "R10.9",
"Score": 0.6904221177101135
},
{
"Description": "Epigastric pain",
"Code": "R10.13",
"Score": 0.1364113688468933
},
{
"Description": "Generalized abdominal pain",
"Code": "R10.84",
"Score": 0.12508003413677216
},
{
"Description": "Left lower quadrant pain",
"Code": "R10.32",
"Score": 0.10063883662223816
},
{
"Description": "Lower abdominal pain, unspecified",
"Code": "R10.30",
"Score": 0.09933677315711975
}
]
},
{
"Id": 1,
"Text": "diabetes",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Score": 0.9899052977561951,
"BeginOffset": 75,
"EndOffset": 83,
"Attributes": [],
"Traits": [
{
"Name": "DIAGNOSIS",
"Score": 0.9258432388305664
}
],
"ICD10CMConcepts": [
{
"Description": "Type 2 diabetes mellitus without complications",
"Code": "E11.9",
"Score": 0.7158446311950684
},
{
"Description": "Family history of diabetes mellitus",
"Code": "Z83.3",
"Score": 0.5704703330993652
},
{
"Description": "Family history of other endocrine, nutritional and metabolic diseases",
"Code": "Z83.49",
"Score": 0.19856023788452148
},
{
"Description": "Type 1 diabetes mellitus with ketoacidosis without coma",
"Code": "E10.10",
"Score": 0.13285516202449799
},
{
"Description": "Type 2 diabetes mellitus with hyperglycemia",
"Code": "E11.65",
"Score": 0.0993388369679451
}
]
}
],
"ModelVersion": "0.1.0"
}
```
Untuk informasi lebih lanjut, lihat [Infer ICD10 -CM di Panduan](https://docs.aws.amazon.com/comprehend/latest/dg/ontology-linking-icd10.html) Pengembang Medis *Amazon Comprehend Medical*.
**Contoh 2: Untuk mendeteksi entitas kondisi medis dan menautkan ke Ontologi ICD-10-CM dari jalur file**
`infer-icd-10-cm`Contoh berikut memberi label pada entitas kondisi medis yang terdeteksi dan menghubungkan entitas tersebut dengan kode dalam edisi 2019 dari International Classification of Diseases Clinical Modification (ICD-10-CM).
```
aws comprehendmedical infer-icd10-cm \
--text file://icd10cm.txt
```
Isi dari `icd10cm.txt`:
```
{
"The patient complains of abdominal pain, has a long-standing history of diabetes treated with Micronase daily."
}
```
Output:
```
{
"Entities": [
{
"Id": 0,
"Text": "abdominal pain",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Score": 0.9475538730621338,
"BeginOffset": 28,
"EndOffset": 42,
"Attributes": [],
"Traits": [
{
"Name": "SYMPTOM",
"Score": 0.6724207401275635
}
],
"ICD10CMConcepts": [
{
"Description": "Unspecified abdominal pain",
"Code": "R10.9",
"Score": 0.6904221177101135
},
{
"Description": "Epigastric pain",
"Code": "R10.13",
"Score": 0.1364113688468933
},
{
"Description": "Generalized abdominal pain",
"Code": "R10.84",
"Score": 0.12508003413677216
},
{
"Description": "Left lower quadrant pain",
"Code": "R10.32",
"Score": 0.10063883662223816
},
{
"Description": "Lower abdominal pain, unspecified",
"Code": "R10.30",
"Score": 0.09933677315711975
}
]
},
{
"Id": 1,
"Text": "diabetes",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Score": 0.9899052977561951,
"BeginOffset": 75,
"EndOffset": 83,
"Attributes": [],
"Traits": [
{
"Name": "DIAGNOSIS",
"Score": 0.9258432388305664
}
],
"ICD10CMConcepts": [
{
"Description": "Type 2 diabetes mellitus without complications",
"Code": "E11.9",
"Score": 0.7158446311950684
},
{
"Description": "Family history of diabetes mellitus",
"Code": "Z83.3",
"Score": 0.5704703330993652
},
{
"Description": "Family history of other endocrine, nutritional and metabolic diseases",
"Code": "Z83.49",
"Score": 0.19856023788452148
},
{
"Description": "Type 1 diabetes mellitus with ketoacidosis without coma",
"Code": "E10.10",
"Score": 0.13285516202449799
},
{
"Description": "Type 2 diabetes mellitus with hyperglycemia",
"Code": "E11.65",
"Score": 0.0993388369679451
}
]
}
],
"ModelVersion": "0.1.0"
}
```
Untuk informasi lebih lanjut, lihat [Menyimpulkan- ICD10 -CM di Panduan Pengembang](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontology-icd10.html) Medis *Amazon Comprehend Medical*.
+ Untuk detail API, lihat [InferIcd10Cm](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/infer-icd10-cm.html) di *Referensi AWS CLI Perintah*.
### `infer-rx-norm`
Contoh kode berikut menunjukkan cara menggunakan`infer-rx-norm`.
**AWS CLI**
**Contoh 1: Untuk mendeteksi entitas obat dan menautkan RxNorm langsung dari teks**
`infer-rx-norm`Contoh berikut menunjukkan dan memberi label entitas obat yang terdeteksi dan menghubungkan entitas tersebut ke pengidentifikasi konsep (RxCui) dari database Perpustakaan Kedokteran Nasional. RxNorm
```
aws comprehendmedical infer-rx-norm \
--text "Patient reports taking Levothyroxine 125 micrograms p.o. once daily, but denies taking Synthroid."
```
Output:
```
{
"Entities": [
{
"Id": 0,
"Text": "Levothyroxine",
"Category": "MEDICATION",
"Type": "GENERIC_NAME",
"Score": 0.9996285438537598,
"BeginOffset": 23,
"EndOffset": 36,
"Attributes": [
{
"Type": "DOSAGE",
"Score": 0.9892290830612183,
"RelationshipScore": 0.9997978806495667,
"Id": 1,
"BeginOffset": 37,
"EndOffset": 51,
"Text": "125 micrograms",
"Traits": []
},
{
"Type": "ROUTE_OR_MODE",
"Score": 0.9988924860954285,
"RelationshipScore": 0.998291552066803,
"Id": 2,
"BeginOffset": 52,
"EndOffset": 56,
"Text": "p.o.",
"Traits": []
},
{
"Type": "FREQUENCY",
"Score": 0.9953463673591614,
"RelationshipScore": 0.9999889135360718,
"Id": 3,
"BeginOffset": 57,
"EndOffset": 67,
"Text": "once daily",
"Traits": []
}
],
"Traits": [],
"RxNormConcepts": [
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet",
"Code": "966224",
"Score": 0.9912070631980896
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Capsule",
"Code": "966405",
"Score": 0.8698278665542603
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet [Synthroid]",
"Code": "966191",
"Score": 0.7448257803916931
},
{
"Description": "levothyroxine",
"Code": "10582",
"Score": 0.7050482630729675
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet [Levoxyl]",
"Code": "966190",
"Score": 0.6921631693840027
}
]
},
{
"Id": 4,
"Text": "Synthroid",
"Category": "MEDICATION",
"Type": "BRAND_NAME",
"Score": 0.9946461319923401,
"BeginOffset": 86,
"EndOffset": 95,
"Attributes": [],
"Traits": [
{
"Name": "NEGATION",
"Score": 0.5167351961135864
}
],
"RxNormConcepts": [
{
"Description": "Synthroid",
"Code": "224920",
"Score": 0.9462039470672607
},
{
"Description": "Levothyroxine Sodium 0.088 MG Oral Tablet [Synthroid]",
"Code": "966282",
"Score": 0.8309829235076904
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet [Synthroid]",
"Code": "966191",
"Score": 0.4945160448551178
},
{
"Description": "Levothyroxine Sodium 0.05 MG Oral Tablet [Synthroid]",
"Code": "966247",
"Score": 0.3674522042274475
},
{
"Description": "Levothyroxine Sodium 0.025 MG Oral Tablet [Synthroid]",
"Code": "966158",
"Score": 0.2588822841644287
}
]
}
],
"ModelVersion": "0.0.0"
}
```
Untuk informasi lebih lanjut, lihat [Menyimpulkan RxNorm](https://docs.aws.amazon.com/comprehend/latest/dg/ontology-linking-rxnorm.html) di *Amazon Comprehend Medical Developer Guide*.
**Contoh 2: Untuk mendeteksi entitas obat dan menautkan ke RxNorm dari jalur file.**
`infer-rx-norm`Contoh berikut menunjukkan dan memberi label entitas obat yang terdeteksi dan menghubungkan entitas tersebut ke pengidentifikasi konsep (RxCui) dari database Perpustakaan Kedokteran Nasional. RxNorm
```
aws comprehendmedical infer-rx-norm \
--text file://rxnorm.txt
```
Isi dari `rxnorm.txt`:
```
{
"Patient reports taking Levothyroxine 125 micrograms p.o. once daily, but denies taking Synthroid."
}
```
Output:
```
{
"Entities": [
{
"Id": 0,
"Text": "Levothyroxine",
"Category": "MEDICATION",
"Type": "GENERIC_NAME",
"Score": 0.9996285438537598,
"BeginOffset": 23,
"EndOffset": 36,
"Attributes": [
{
"Type": "DOSAGE",
"Score": 0.9892290830612183,
"RelationshipScore": 0.9997978806495667,
"Id": 1,
"BeginOffset": 37,
"EndOffset": 51,
"Text": "125 micrograms",
"Traits": []
},
{
"Type": "ROUTE_OR_MODE",
"Score": 0.9988924860954285,
"RelationshipScore": 0.998291552066803,
"Id": 2,
"BeginOffset": 52,
"EndOffset": 56,
"Text": "p.o.",
"Traits": []
},
{
"Type": "FREQUENCY",
"Score": 0.9953463673591614,
"RelationshipScore": 0.9999889135360718,
"Id": 3,
"BeginOffset": 57,
"EndOffset": 67,
"Text": "once daily",
"Traits": []
}
],
"Traits": [],
"RxNormConcepts": [
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet",
"Code": "966224",
"Score": 0.9912070631980896
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Capsule",
"Code": "966405",
"Score": 0.8698278665542603
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet [Synthroid]",
"Code": "966191",
"Score": 0.7448257803916931
},
{
"Description": "levothyroxine",
"Code": "10582",
"Score": 0.7050482630729675
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet [Levoxyl]",
"Code": "966190",
"Score": 0.6921631693840027
}
]
},
{
"Id": 4,
"Text": "Synthroid",
"Category": "MEDICATION",
"Type": "BRAND_NAME",
"Score": 0.9946461319923401,
"BeginOffset": 86,
"EndOffset": 95,
"Attributes": [],
"Traits": [
{
"Name": "NEGATION",
"Score": 0.5167351961135864
}
],
"RxNormConcepts": [
{
"Description": "Synthroid",
"Code": "224920",
"Score": 0.9462039470672607
},
{
"Description": "Levothyroxine Sodium 0.088 MG Oral Tablet [Synthroid]",
"Code": "966282",
"Score": 0.8309829235076904
},
{
"Description": "Levothyroxine Sodium 0.125 MG Oral Tablet [Synthroid]",
"Code": "966191",
"Score": 0.4945160448551178
},
{
"Description": "Levothyroxine Sodium 0.05 MG Oral Tablet [Synthroid]",
"Code": "966247",
"Score": 0.3674522042274475
},
{
"Description": "Levothyroxine Sodium 0.025 MG Oral Tablet [Synthroid]",
"Code": "966158",
"Score": 0.2588822841644287
}
]
}
],
"ModelVersion": "0.0.0"
}
```
Untuk informasi lebih lanjut, lihat [Menyimpulkan RxNorm](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontology-RxNorm.html) di *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [InferRxNorm](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/infer-rx-norm.html)di *Referensi AWS CLI Perintah*.
### `infer-snomedct`
Contoh kode berikut menunjukkan cara menggunakan`infer-snomedct`.
**AWS CLI**
**Contoh: Untuk mendeteksi entitas dan menautkan ke SNOMED CT Ontology langsung dari teks**
`infer-snomedct`Contoh berikut menunjukkan cara mendeteksi entitas medis dan menghubungkannya dengan konsep dari versi 2021-03 dari Nomenklatur Kedokteran Sistematisasi, Istilah Klinis (SNOMED CT).
```
aws comprehendmedical infer-snomedct \
--text "The patient complains of abdominal pain, has a long-standing history of diabetes treated with Micronase daily."
```
Output:
```
{
"Entities": [
{
"Id": 3,
"BeginOffset": 26,
"EndOffset": 40,
"Score": 0.9598260521888733,
"Text": "abdominal pain",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Traits": [
{
"Name": "SYMPTOM",
"Score": 0.6819021701812744
}
]
},
{
"Id": 4,
"BeginOffset": 73,
"EndOffset": 81,
"Score": 0.9905840158462524,
"Text": "diabetes",
"Category": "MEDICAL_CONDITION",
"Type": "DX_NAME",
"Traits": [
{
"Name": "DIAGNOSIS",
"Score": 0.9255214333534241
}
]
},
{
"Id": 1,
"BeginOffset": 95,
"EndOffset": 104,
"Score": 0.6371926665306091,
"Text": "Micronase",
"Category": "MEDICATION",
"Type": "BRAND_NAME",
"Traits": [],
"Attributes": [
{
"Type": "FREQUENCY",
"Score": 0.9761165380477905,
"RelationshipScore": 0.9984188079833984,
"RelationshipType": "FREQUENCY",
"Id": 2,
"BeginOffset": 105,
"EndOffset": 110,
"Text": "daily",
"Category": "MEDICATION",
"Traits": []
}
]
}
],
"UnmappedAttributes": [],
"ModelVersion": "1.0.0"
}
```
*Untuk informasi lebih lanjut, lihat [InfersNoMEDCT](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontology-linking-snomed.html) di Amazon Comprehend Medical Developer Guide.*
+ Untuk detail API, lihat [InferSnomedct](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/infer-snomedct.html)di *Referensi AWS CLI Perintah*.
### `list-entities-detection-v2-jobs`
Contoh kode berikut menunjukkan cara menggunakan`list-entities-detection-v2-jobs`.
**AWS CLI**
**Untuk mencantumkan pekerjaan deteksi entitas**
`list-entities-detection-v2-jobs`Contoh berikut mencantumkan pekerjaan deteksi asinkron saat ini.
```
aws comprehendmedical list-entities-detection-v2-jobs
```
Output:
```
{
"ComprehendMedicalAsyncJobPropertiesList": [
{
"JobId": "ab9887877365fe70299089371c043b96",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-03-19T20:38:37.594000+00:00",
"EndTime": "2020-03-19T20:45:07.894000+00:00",
"ExpirationTime": "2020-07-17T20:38:37+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": ""
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "867139942017-EntitiesDetection-ab9887877365fe70299089371c043b96/"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "DetectEntitiesModelV20190930"
}
]
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [ListEntitiesDetectionV2Jobs](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/list-entities-detection-v2-jobs.html) di Referensi *AWS CLI Perintah*.
### `list-icd10-cm-inference-jobs`
Contoh kode berikut menunjukkan cara menggunakan`list-icd10-cm-inference-jobs`.
**AWS CLI**
**Untuk membuat daftar semua pekerjaan inferensi ICD-10-CM saat ini**
Contoh berikut menunjukkan bagaimana `list-icd10-cm-inference-jobs` operasi mengembalikan daftar pekerjaan inferensi batch ICD-10-CM asinkron saat ini.
```
aws comprehendmedical list-icd10-cm-inference-jobs
```
Output:
```
{
"ComprehendMedicalAsyncJobPropertiesList": [
{
"JobId": "5780034166536cdb52ffa3295a1b00a7",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-05-19T20:38:37.594000+00:00",
"EndTime": "2020-05-19T20:45:07.894000+00:00",
"ExpirationTime": "2020-09-17T20:38:37+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "0.1.0"
}
]
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [ListIcd10 CmInferenceJobs](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/list-icd10-cm-inference-jobs.html) di *Referensi AWS CLI Perintah*.
### `list-phi-detection-jobs`
Contoh kode berikut menunjukkan cara menggunakan`list-phi-detection-jobs`.
**AWS CLI**
**Untuk membuat daftar pekerjaan deteksi informasi kesehatan yang dilindungi (PHI)**
`list-phi-detection-jobs`Contoh berikut mencantumkan pekerjaan deteksi informasi kesehatan terlindungi (PHI) saat ini
```
aws comprehendmedical list-phi-detection-jobs
```
Output:
```
{
"ComprehendMedicalAsyncJobPropertiesList": [
{
"JobId": "4750034166536cdb52ffa3295a1b00a3",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-03-19T20:38:37.594000+00:00",
"EndTime": "2020-03-19T20:45:07.894000+00:00",
"ExpirationTime": "2020-07-17T20:38:37+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": ""
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "867139942017-PHIDetection-4750034166536cdb52ffa3295a1b00a3/"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "PHIModelV20190903"
}
]
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [ListPhiDetectionJobs](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/list-phi-detection-jobs.html)di *Referensi AWS CLI Perintah*.
### `list-rx-norm-inference-jobs`
Contoh kode berikut menunjukkan cara menggunakan`list-rx-norm-inference-jobs`.
**AWS CLI**
**Untuk membuat daftar semua pekerjaan inferensi Rx-Norm saat ini**
Contoh berikut menunjukkan bagaimana `list-rx-norm-inference-jobs` mengembalikan daftar pekerjaan inferensi batch Rx-Norm asinkron saat ini.
```
aws comprehendmedical list-rx-norm-inference-jobs
```
Output:
```
{
"ComprehendMedicalAsyncJobPropertiesList": [
{
"JobId": "4980034166536cfb52gga3295a1b00a3",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-05-19T20:38:37.594000+00:00",
"EndTime": "2020-05-19T20:45:07.894000+00:00",
"ExpirationTime": "2020-09-17T20:38:37+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "0.0.0"
}
]
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [ListRxNormInferenceJobs](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/list-rx-norm-inference-jobs.html)di *Referensi AWS CLI Perintah*.
### `list-snomedct-inference-jobs`
Contoh kode berikut menunjukkan cara menggunakan`list-snomedct-inference-jobs`.
**AWS CLI**
**Untuk membuat daftar semua pekerjaan inferensi CT SNOMED**
Contoh berikut menunjukkan bagaimana `list-snomedct-inference-jobs` operasi mengembalikan daftar pekerjaan inferensi batch SNOMED CT asinkron saat ini.
```
aws comprehendmedical list-snomedct-inference-jobs
```
Output:
```
{
"ComprehendMedicalAsyncJobPropertiesList": [
{
"JobId": "5780034166536cdb52ffa3295a1b00a7",
"JobStatus": "COMPLETED",
"SubmitTime": "2020-05-19T20:38:37.594000+00:00",
"EndTime": "2020-05-19T20:45:07.894000+00:00",
"ExpirationTime": "2020-09-17T20:38:37+00:00",
"InputDataConfig": {
"S3Bucket": "comp-med-input",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"OutputDataConfig": {
"S3Bucket": "comp-med-output",
"S3Key": "AKIAIOSFODNN7EXAMPLE"
},
"LanguageCode": "en",
"DataAccessRoleArn": "arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole",
"ModelVersion": "0.1.0"
}
]
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [ListSnomedctInferenceJobs](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/list-snomedct-inference-jobs.html)di *Referensi AWS CLI Perintah*.
### `start-entities-detection-v2-job`
Contoh kode berikut menunjukkan cara menggunakan`start-entities-detection-v2-job`.
**AWS CLI**
**Untuk memulai pekerjaan deteksi entitas**
`start-entities-detection-v2-job`Contoh berikut memulai pekerjaan deteksi entitas asinkron.
```
aws comprehendmedical start-entities-detection-v2-job \
--input-data-config "S3Bucket=comp-med-input" \
--output-data-config "S3Bucket=comp-med-output" \
--data-access-role-arn arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole \
--language-code en
```
Output:
```
{
"JobId": "ab9887877365fe70299089371c043b96"
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [StartEntitiesDetectionV2Job](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/start-entities-detection-v2-job.html) di Referensi *AWS CLI Perintah*.
### `start-icd10-cm-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`start-icd10-cm-inference-job`.
**AWS CLI**
**Untuk memulai pekerjaan inferensi ICD-10-CM**
`start-icd10-cm-inference-job`Contoh berikut memulai pekerjaan analisis batch inferensi ICD-10-CM.
```
aws comprehendmedical start-icd10-cm-inference-job \
--input-data-config "S3Bucket=comp-med-input" \
--output-data-config "S3Bucket=comp-med-output" \
--data-access-role-arn arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole \
--language-code en
```
Output:
```
{
"JobId": "ef7289877365fc70299089371c043b96"
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [StartIcd10 CmInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/start-icd10-cm-inference-job.html) di *Referensi AWS CLI Perintah*.
### `start-phi-detection-job`
Contoh kode berikut menunjukkan cara menggunakan`start-phi-detection-job`.
**AWS CLI**
**Untuk memulai pekerjaan deteksi PHI**
`start-phi-detection-job`Contoh berikut memulai pekerjaan deteksi entitas PHI asinkron.
```
aws comprehendmedical start-phi-detection-job \
--input-data-config "S3Bucket=comp-med-input" \
--output-data-config "S3Bucket=comp-med-output" \
--data-access-role-arn arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole \
--language-code en
```
Output:
```
{
"JobId": "ab9887877365fe70299089371c043b96"
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [StartPhiDetectionJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/start-phi-detection-job.html)di *Referensi AWS CLI Perintah*.
### `start-rx-norm-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`start-rx-norm-inference-job`.
**AWS CLI**
**Untuk memulai pekerjaan RxNorm inferensi**
`start-rx-norm-inference-job`Contoh berikut memulai pekerjaan analisis batch RxNorm inferensi.
```
aws comprehendmedical start-rx-norm-inference-job \
--input-data-config "S3Bucket=comp-med-input" \
--output-data-config "S3Bucket=comp-med-output" \
--data-access-role-arn arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole \
--language-code en
```
Output:
```
{
"JobId": "eg8199877365fc70299089371c043b96"
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [StartRxNormInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/start-rx-norm-inference-job.html)di *Referensi AWS CLI Perintah*.
### `start-snomedct-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`start-snomedct-inference-job`.
**AWS CLI**
**Untuk memulai pekerjaan inferensi CT SNOMED**
`start-snomedct-inference-job`Contoh berikut memulai pekerjaan analisis batch inferensi CT SNOMED.
```
aws comprehendmedical start-snomedct-inference-job \
--input-data-config "S3Bucket=comp-med-input" \
--output-data-config "S3Bucket=comp-med-output" \
--data-access-role-arn arn:aws:iam::867139942017:role/ComprehendMedicalBatchProcessingRole \
--language-code en
```
Output:
```
{
"JobId": "dg7289877365fc70299089371c043b96"
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [StartSnomedctInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/start-snomedct-inference-job.html)di *Referensi AWS CLI Perintah*.
### `stop-entities-detection-v2-job`
Contoh kode berikut menunjukkan cara menggunakan`stop-entities-detection-v2-job`.
**AWS CLI**
**Untuk menghentikan pekerjaan deteksi entitas**
`stop-entities-detection-v2-job`Contoh berikut menghentikan pekerjaan deteksi entitas asinkron.
```
aws comprehendmedical stop-entities-detection-v2-job \
--job-id "ab9887877365fe70299089371c043b96"
```
Output:
```
{
"JobId": "ab9887877365fe70299089371c043b96"
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [StopEntitiesDetectionV2Job](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/stop-entities-detection-v2-job.html) di Referensi *AWS CLI Perintah*.
### `stop-icd10-cm-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`stop-icd10-cm-inference-job`.
**AWS CLI**
**Untuk menghentikan pekerjaan inferensi ICD-10-CM**
`stop-icd10-cm-inference-job`Contoh berikut menghentikan pekerjaan analisis batch inferensi ICD-10-CM.
```
aws comprehendmedical stop-icd10-cm-inference-job \
--job-id "4750034166536cdb52ffa3295a1b00a3"
```
Output:
```
{
"JobId": "ef7289877365fc70299089371c043b96",
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [StopIcd10 CmInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/stop-icd10-cm-inference-job.html) di *Referensi AWS CLI Perintah*.
### `stop-phi-detection-job`
Contoh kode berikut menunjukkan cara menggunakan`stop-phi-detection-job`.
**AWS CLI**
**Untuk menghentikan pekerjaan deteksi informasi kesehatan yang dilindungi (PHI)**
`stop-phi-detection-job`Contoh berikut menghentikan pekerjaan deteksi informasi kesehatan terlindungi asinkron (PHI).
```
aws comprehendmedical stop-phi-detection-job \
--job-id "4750034166536cdb52ffa3295a1b00a3"
```
Output:
```
{
"JobId": "ab9887877365fe70299089371c043b96"
}
```
Untuk informasi selengkapnya, lihat [Batch APIs](https://docs.aws.amazon.com/comprehend-medical/latest/dev/textanalysis-batchapi.html) in the *Amazon Comprehend Medical Developer Guide*.
+ Untuk detail API, lihat [StopPhiDetectionJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/stop-phi-detection-job.html)di *Referensi AWS CLI Perintah*.
### `stop-rx-norm-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`stop-rx-norm-inference-job`.
**AWS CLI**
**Untuk menghentikan pekerjaan RxNorm inferensi**
`stop-rx-norm-inference-job`Contoh berikut menghentikan pekerjaan analisis batch inferensi ICD-10-CM.
```
aws comprehendmedical stop-rx-norm-inference-job \
--job-id "eg8199877365fc70299089371c043b96"
```
Output:
```
{
"JobId": "eg8199877365fc70299089371c043b96",
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [StopRxNormInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/stop-rx-norm-inference-job.html)di *Referensi AWS CLI Perintah*.
### `stop-snomedct-inference-job`
Contoh kode berikut menunjukkan cara menggunakan`stop-snomedct-inference-job`.
**AWS CLI**
**Untuk menghentikan pekerjaan inferensi CT SNOMED**
`stop-snomedct-inference-job`Contoh berikut menghentikan pekerjaan analisis batch inferensi CT SNOMED.
```
aws comprehendmedical stop-snomedct-inference-job \
--job-id "8750034166436cdb52ffa3295a1b00a1"
```
Output:
```
{
"JobId": "8750034166436cdb52ffa3295a1b00a1",
}
```
Untuk informasi selengkapnya, lihat [Ontologi yang menghubungkan analisis batch](https://docs.aws.amazon.com/comprehend-medical/latest/dev/ontologies-batchapi.html) di *Amazon Comprehend Medical* Developer Guide.
+ Untuk detail API, lihat [StopSnomedctInferenceJob](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/comprehendmedical/stop-snomedct-inference-job.html)di *Referensi AWS CLI Perintah*.