Apollo Hospitals PreAnesthesia AI

• A machine learning model developed using Indian data demonstrates higher accuracy than conventional risk scores.
• Feedback Loop from the prospective use in patients
• Comprehensive AI-augmented pathway
• Validated at different National Institutions
• Integrated Clinical Decision Support Tool (What Next to Do)
• QMS: ISO 13485:2016 Certified, MDSAP Certification (In process)

Interpretation & Adoption Message

• AI Algorithm + clinicians: This risk assessment tool has been built as an adjunct tool for physicians to estimate key surgical outcomes for patients during pre-anesthesia checks.
• Risk Identification and Clinical Decision Trajectories: This risk assessment tool estimates surgical duration, blood loss, and post-operative patient placement by analyzing clinical and laboratory parameters during the pre-anesthesia assessment. Built to support low-cost settings, the model aims to optimize resource allocation and enhance procedural efficiency.
• Where to use: The Pre-Anesthesia AI model has been designed for application across all departments for patients admitted for surgical procedures.