HealthAI has not lived up to its potential.

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.

Until now.

Bayesian makes proactive care possible.

Intelligent Care Augmentation – Increasing the Capacity of Clinicians to Visualize & Address Patient Risk

Bayesian Health’s AI platform sits within a hospital’s Electronic Medical Records (EMR) system where it analyzes patient data, sending accurate and actionable clinical signals within existing workflows to empower physicians and care team members to catch life-threatening complications early.


Bayesian directs the attention of the clinician to patients at high risk. Clinicians are encouraged to interact with Bayesian and they don’t feel pressure to always agree with it. Bayesian’s AI thinks like a clinician by considering multiple data points in concert rather than individually. Clinicians use the platform as an extra set of eyes and ears. To illustrate this concept, think of a provider or nurse weighing all the available data (labs and vitals from the last 48h, patient medical history etc.) and making a decision about a patient’s risk status. Bayesian is a silent colleague continuously reviewing all the data and calling attention to what matters most.

With high-physician adoption, Bayesian’s real-time clinical signals drive faster, timelier treatment and better care outcomes.

Recent, large outcome study showed 89% physician and care team adoption, leading to 1.85h earlier treatment for sepsis.


Patient-specific, targeted


Signals arrive with clinically meaningful lead time


Rigorously tested, proven


Structured to reduce bias and false signals


Context accompanies every signal for transparency

Targeting life-threatening conditions where early detection leads to meaningful clinical and financial impact.

Read about how Bayesian achieved improved clinical and financial outcomes for one health system, driven by high adoption and continued engagement of the platform.

What sets Bayesian apart

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.

Learn more about how Bayesian Health can enable proactive care at your health system.

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