AI in Healthcare: How To Assess What Works
At ViVE 2025, healthcare leaders emphasized that AI scribes are proving effective and scalable, especially in reducing physician burnout, while broader clinical AI tools still face challenges around reliability and integration. Speakers urged health systems to focus on long-term value, ease of use, and real-world outcomes over hype when evaluating AI solutions.
Elon Musk asked People to Upload Their Health Data. X Users Obliged
Users on X have begun uploading personal medical images to Grok, an AI chatbot, raising concerns about data privacy and clinical accuracy. Bayesian Health founder Suchi Saria cautioned that without high-quality data and medical expertise, efforts like these risk becoming amateur experiments rather than delivering meaningful, safe health insights.
Artificial intelligence was a hot-button topic at Modern Healthcare’s Digital
At Modern Healthcare’s Digital Health Summit, AI took center stage as leaders debated its promise, risks, and readiness for clinical care. Companies like Bayesian Health continue to stand out by demonstrating real-world impact through clinically validated, scalable AI applications designed to improve outcomes without overwhelming frontline teams.
Bayesian Health was named to TIME’s Best Inventions of 2024 for its AI platform that helps prevent pressure ulcers in hospitals. The system analyzes electronic medical records to identify at-risk patients early, enabling proactive and preventative care.
Cleveland Clinic is gearing up for the integration of artificial intelligence across its operations, with a focus on both clinical and nonclinical applications.
Cleveland Clinic is piloting AI in key areas including sepsis risk prediction, documentation, and coding automation, with a strong focus on ethical oversight and frontline integration. Among its partners is Bayesian Health, whose clinically validated platform supports early identification of high-risk patients, aligning with the system’s long-term strategy for AI-driven care optimization.
AI Model Improves Early Detection of Hospital-Acquired Pressure Injuries
A collaborative study by USC, Johns Hopkins, and University Hospitals developed an AI model that significantly outperforms traditional tools in predicting hospital-acquired pressure injuries. Bayesian Health, led by Dr. Suchi Saria, contributed to the work, showcasing how its platform improves early detection, reduces nursing burden, and advances health equity through unbiased, data-driven risk assessment.
2023 was a transformative year for Bayesian Health and clinical AI. Following significant achievements like FDA recognition and major EMR integrations, Bayesian established itself as a leader in healthcare technology.
Delve into our Year in Review page to uncover the pivotal moments and strategic partnerships that thrust Bayesian into the industry forefront, shaping the trajectory of clinical AI. Join us to explore how these elements coalesced to make 2023 a defining year for Bayesian in the realm of healthcare technology.
