Digital Twin approach to Clinical DSS with Explainable AI

Understand

We propose a digital twin approach to improve healthcare decision support systems with a combination of domain knowledge and data.

• Domain knowledge helps build decision thresholds that doctors can use to determine a risk or recommend a treatment or test based on the specific patient condition.
• However, these assessments tend to be highly subjective and differ from doctor to doctor and from patient to patient.
• We propose a system where we collate this subjective risk by compiling data from different doctors treating different patients and build a machine learning model that learns from this knowledge.