AI-900: Efficient Insurance Claim Processing: Leveraging Natural Language Processing for Key Term Extraction

Discover the ideal AI workload for extracting key terms from insurance claim reports and generating summaries. Explore the benefits and capabilities of conversational AI, anomaly detection, natural language processing, and computer vision. Streamline your insurance claim processing by harnessing the power of natural language processing to extract crucial information and enhance efficiency.

Question

You have insurance claim reports that are stored as text. You need to extract key terms from the reports to generate summaries. Which type of Al workload should you use?

A. conversational Al
B. anomaly detection
C. natural language processing
D. computer vision

Answer

C. natural language processing

Explanation

The correct answer is C. natural language processing.

Natural language processing (NLP) is a type of Al workload that deals with analyzing, understanding, and generating natural language text or speech. NLP can be used for various tasks such as sentiment analysis, text summarization, machine translation, named entity recognition, question answering, and more.

In this scenario, you need to extract key terms from the insurance claim reports that are stored as text and generate summaries. This is an example of text summarization, which is a subtask of NLP. Text summarization aims to produce a concise and coherent summary of a longer text document by extracting the most important information and discarding the irrelevant details. Text summarization can be done in two ways: extractive or abstractive. Extractive summarization selects the most salient sentences or phrases from the original text and concatenates them to form a summary. Abstractive summarization generates new sentences or phrases that capture the main idea of the original text.

Therefore, to perform text summarization on the insurance claim reports, you should use natural language processing as the type of Al workload.

Key phrase extraction is the concept of evaluating the text of a document, or documents, and then identifying the main talking points of the document(s). Key phase extraction is a part of Text Analytics. The Text Analytics service is a part of the Azure Cognitive Services offerings that can perform advanced natural language processing over raw text.

References

Microsoft Docs > Microsoft Azure AI Fundamentals: Explore natural language processing > Analyze text with the Language service > Get started with text analysis

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