This AI-102 practice question tests your understanding of implement natural language processing solutions. 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 organization uses Azure AI Language to analyze clinical notes. They need to detect protected health information (PHI) such as patient names and dates of birth, and also identify medical conditions. Which Azure AI Language feature should they use?
Conversation Analysis
Why wrong: Designed for conversational data, not clinical notes.
Custom Text Classification
Why wrong: Requires custom training and does not detect PHI out of the box.
Text Analytics for health (general availability)
Why wrong: GA version does not include PHI detection.
Health Text Analytics (preview) in Azure AI Language
This feature includes PHI detection and medical entity recognition.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
Health Text Analytics (preview) in Azure AI Language
Option A is correct because the Azure AI Language Health Text Analytics (preview) includes both PHI detection and medical entity recognition. Option B is wrong because the standard Text Analytics for health does not include PHI detection. Option C is wrong because the Conversation Analysis feature is for conversational data, not clinical notes. Option D is wrong because Custom Text Classification does not detect PHI or medical conditions out of the box.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
Conversation Analysis
Why it's wrong here
Designed for conversational data, not clinical notes.
Custom Text Classification
Why it's wrong here
Requires custom training and does not detect PHI out of the box.
Text Analytics for health (general availability)
Why it's wrong here
GA version does not include PHI detection.
Health Text Analytics (preview) in Azure AI Language
Why this is correct
This feature includes PHI detection and medical entity recognition.
Related concept
Static NAT maps one inside address to one outside address.
Common exam traps
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
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FAQ
Implement natural language processing solutions — This question tests Implement natural language processing solutions — Static NAT maps one inside address to one outside address..
The correct answer is: Health Text Analytics (preview) in Azure AI Language — Option A is correct because the Azure AI Language Health Text Analytics (preview) includes both PHI detection and medical entity recognition. Option B is wrong because the standard Text Analytics for health does not include PHI detection. Option C is wrong because the Conversation Analysis feature is for conversational data, not clinical notes. Option D is wrong because Custom Text Classification does not detect PHI or medical conditions out of the box.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related AI-102 NAT questions on configuration and troubleshooting.
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 20, 2026
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