Artificial intelligence powered Large Language Models (LLMs) matched and outperformed medical practitioners in select controlled tests with regards to patient diagnosis and treatment plan formulations, according to two studies from the Nature journal on Wednesday.
This seems to indicate that LLMs have displayed notable improvement in their capabilities for providing appropriate medical advice and insights. The research papers noted that despite their improvements, they still needed further work and additional research to establish safety and governance standards along with real world applications.
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The studies covered MIRA (Medical Intelligence for Reasoning and Action) and Google's AMIE (Articulate Medical Intelligence Explorer) systems and ran simulations to gauge them for their diagnosis capabilities.
MIRA was given access to select electronic health records in a controlled test where researchers had it use the data to provide diagnosis for over 500 emergenc department cases, where it outperformed doctors with an accuracy of 87.1% compared to their 78.1%.
"In simulations on real patient cases spanning multiple diagnoses, MIRA outperformed physicians in diagnostic accuracy and made guideline-concordant, medication-safe and appropriate admission decisions," the study stated.
The study contended that the AI needs to be tested with "real world" studies to further establish standards.
"Further work is needed to establish generalization, safety and governance through prospective, real-world studies," the study said.
AMIE was evaluated based on its ability to interact with patients and determine an appropriate treatment plan for them. As per the researchers, the AI's treatment plans aligned closer to established clinical guidelines in comparison to 21 practicing doctors in the UK.
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The report stated that AMIE requires further research for real-world application and that it's accuracy shows improvement in LLM's aiding in disease control.
"While further research would be needed before real-world translation, AMIE's strong performance across evaluations marks a significant step towards conversational AI as a tool in disease management," the report said.
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