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About Artificial Intelligence in Health Care: Reducing Administrative Burden
This document discusses using artificial intelligence and machine learning techniques like deep learning neural networks to help reduce administrative burden in health care. It provides examples of how rules-based decision making, statistical reasoning, machine learning, and artificial intelligence have increasingly been used to analyze complex medical data. Recent research demonstrates that deep learning models trained on large medical image and text datasets can successfully perform tasks like detecting skin cancers, interpreting medical scans, and identifying arrhythmias from ECG readings. The document suggests administrative processes that involve analyzing large amounts of unstructured text data from medical records may also be well-suited for deep learning approaches. It emphasizes the importance of ongoing evaluation and refinement of any AI or machine learning models implemented in health care.
Detailed Information
| Author: | ['Dharshan Kumar'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 8 |
| Language: | English |
| Format: | |
| Price: | FREE |
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