NEW YORK--(BUSINESS WIRE)--K Health, the clinical Artificial Intelligence (AI), 24/7 national primary care provider, today announces the publication of peer-reviewed research titled "Diagnostic Accuracy of Artificial Intelligence in Virtual Primary Care". The large-scale research compared K’s clinical AI diagnostic capability with the actual diagnosis clinicians gave to patients on K virtual primary care platform. This comprehensive study of over 102,000 real-world primary care clinical cases was co-authored by Dan Zeltzer, Princeton University-trained Health Economist from Tel Aviv University, and Jon O Ebbert, M.D., Professor of Medicine at Mayo Clinic.

The study’s key findings:

Clinicians providing clinical care to real-life patients agreed with the AI-generated diagnoses 84.2% of the time.
In 57 of the most common primary care diagnoses, more than 90% agreement existed between AI-generated and clinician differential diagnoses.
Independent clinicians adjudicators blind to the source of the diagnosis, chose K’s AI differential diagnosis as often as the clinician’s diagnosis.
Adjudicator consensus diagnosis was always in the AI differential diagnosis.
The study also demonstrates how the AI can improve from the clinician’s feedback in a unique reinforcement learning loop.
The study observed no biases across gender, age and ethnicity in the AI-generated differential diagnoses.
AI holds the potential to revolutionize decision-making in healthcare, but has been understudied in primary care, until now. The study results show AI's strong accuracy in primary care, with the possibility for AI to assist in pre-visit medical intake and differential diagnosis.

“When clinical cases were independently reviewed by three experts, the AI-generated list of possible diagnoses included the diagnosis most experts agreed on in every case,” said Dr. Ebbert. “We also observed that retraining can improve the performance of these AI models.”

K created a primary care platform that uses proprietary AI models trained on clinical data, such as data from the Mayo Clinic Platform_Discover, combined with doctor oversight, enabling widespread access to quality clinical care. K’s clinical AI enables K’s clinicians to make high-quality medical decisions. K’s close-looped reinforcement model allows K’s AI to learn from the data and under clinical supervision, improve its predictive algorithms.

“We have built a clinical-grade AI system that works with a 24/7 primary care clinic,” said Ran Shaul, Co-Founder and Chief Product Officer. “As our AI learns from data and becomes smarter, it can make a huge difference in terms of saving doctors’ time and providing doctors with AI superpowers at their fingertips. As a next step, we are in the process of integrating our platform and service into points of care at leading health systems.”

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