Historically, AI-driven clinical decision support models were not able to effectively monitor, tune and improve their performance over time. Due to these limitations, legacy healthAI has grown to be associated with lower accuracy, higher false-alerting rates (leading to alarm fatigue) and higher instances of over-treatment.
Signals arrive with clinically meaningful lead time
Rigorously tested, proven
Structured to reduce bias and false signals
Context accompanies every signal for transparency
Read about how Bayesian achieved improved clinical and financial outcomes for one health system, driven by high adoption and continued engagement of the platform.
Decades of published research has validated our machine learning strategies, and over two years at academic and community hospitals has validated our adoption, engagement, and outcomes.
08/11/22 Becker’s Hospital Review – Early warnings, few false alerts: What physicians want out of AI sepsis ...08 August, 2022