The healthcare industry has seen rapid advances in artificial intelligence and machine learning capabilities in recent years—from virtual health assistants and drug discovery to development and personalized medicine. These advancements are transforming healthcare, making it more efficient, personalized and more effective.
By training on extensive medical texts, these AI models can accurately identify relevant codes and quality measures, streamlining the process of documentation and billing and helping ensure compliance with healthcare standards.Shai Gilgeous-Alexander’s Quad Injury Could Impact Close To Thunder’s Season
Data integration and terminology challenges also continue to hinder the application of AI for quality coding. The multitude of diagnosis code systems like ICD, CPT, SNOMED and RxNorm have differing formats that do not interoperate smoothly. Medical language itself poses another barrier, with complex synonymy, polysemy and negation that AI still struggles to process accurately. Distinguishing between phrases like feeling"cold" due to temperature or illness exemplifies this subtlety.
Source: Healthcare Press (healthcarepress.net)
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