Quick Answer
The answer is Amazon Comprehend Medical. This service is the correct choice because it is purpose-built for PHI detection and masking with Comprehend Medical, using specialized natural language processing to identify entities like patient names, dates, and medical conditions from unstructured clinical text, and it provides APIs to redact that information before output. On the AWS Certified AI Practitioner AIF-C01 exam, this question tests your ability to distinguish between general-purpose NLP services like standard Comprehend and healthcare-specific ones; a common trap is selecting Amazon Bedrock itself or Amazon Textract, but remember that only Comprehend Medical is designed for HIPAA-eligible PHI handling in medical text. For a quick memory tip, think “Medical for medical data”—if the scenario involves patient health information, always look for the word “Medical” in the service name.
This AIF-C01 practice question tests your understanding of applications of foundation models. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A healthcare company uses Amazon Bedrock to generate patient summaries. They need to ensure no protected health information (PHI) is leaked in the output. Which AWS service can they use to detect and mask PHI in text?
Amazon Comprehend Medical
Comprehend Medical can identify and mask PHI such as patient names and dates.
Amazon Macie
Why wrong: Macie discovers sensitive data in Amazon S3, not in real-time model output.
AWS Glue
Why wrong: AWS Glue is a data integration service, not for content moderation.
Amazon Rekognition
Why wrong: Rekognition is for image and video analysis, not for text PHI detection.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Amazon Comprehend Medical
Amazon Comprehend Medical is specifically designed to extract and identify protected health information (PHI) from unstructured medical text using natural language processing (NLP). It can detect entities such as patient names, dates, medical conditions, and medications, and provides APIs to mask or redact that PHI before output. This makes it the correct choice for the healthcare company's requirement to prevent PHI leakage in patient summaries generated by Amazon Bedrock.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Amazon Comprehend Medical
Why this is correct
Comprehend Medical can identify and mask PHI such as patient names and dates.
Related concept
Read the scenario before looking for a memorised answer.
Amazon Macie
Why it's wrong here
Macie discovers sensitive data in Amazon S3, not in real-time model output.
AWS Glue
Why it's wrong here
AWS Glue is a data integration service, not for content moderation.
Amazon Rekognition
Why it's wrong here
Rekognition is for image and video analysis, not for text PHI detection.
Common exam traps
AWS often tests the distinction between general-purpose data protection services (like Macie) and domain-specific medical NLP services (like Comprehend Medical), leading candidates to choose Macie because it is associated with sensitive data discovery, even though it cannot perform inline text masking.
Trap categories for this question
Command / output trap
Macie discovers sensitive data in Amazon S3, not in real-time model output.
Detailed technical explanation
Amazon Comprehend Medical uses a specialized NLP model trained on medical ontologies such as ICD-10-CM, RxNorm, and SNOMED CT to identify clinical entities and PHI. It supports real-time API calls with a maximum payload of 100 KB per request, and the DetectPHI operation returns offsets and confidence scores for each entity, which can be used to mask or redact the text before downstream processing. In a real-world scenario, a healthcare application could chain Bedrock's text generation with a Comprehend Medical PHI detection step to ensure compliance with HIPAA regulations.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
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FAQ
Applications of Foundation Models — This question tests Applications of Foundation Models — Read the scenario before looking for a memorised answer..
The correct answer is: Amazon Comprehend Medical — Amazon Comprehend Medical is specifically designed to extract and identify protected health information (PHI) from unstructured medical text using natural language processing (NLP). It can detect entities such as patient names, dates, medical conditions, and medications, and provides APIs to mask or redact that PHI before output. This makes it the correct choice for the healthcare company's requirement to prevent PHI leakage in patient summaries generated by Amazon Bedrock.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.
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