The model, Dead-end Discovery, uses the reinforcement learning ML framework – where an agent learns from trial and error – because it is well-suited to health care. Health care is characterized by sequential decision-making: After looking at a patient’s condition, providers apply a treatment and observe the results. If the patient improves, the process repeats.
Microsoft’s AI Model Identifies When Medical Treatments Harm More Than Help
