Nan Zhang, Ph.D.

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SUMMARY

Nan Zhang, Ph.D., is a data scientist with expertise in applied data analytics, statistics, machine learning and artificial intelligence. Dr. Zhang's research is focused on applying machine learning approaches to solve complex clinical problems using electronic health records, with the aim of accelerating clinical research and improving patient care in clinical practice. Particularly, she has developed and applied novel causal machine learning models to predict individualized treatment effect of interventions to guide personalized treatment decision-making.

Focus areas

• Personalized treatment decision-making. Instead of utilizing randomized trials to compare the effectiveness of interventions, Dr. Zhang has developed machine learning models to estimate individualized treatment effect from the observational clinical data.

  These methods have been applied to provide personalized treatment options for people with atrial fibrillation. In this study, machine learning models were utilized to guide treatment decision-making comparing an implanted device, Watchman, to other stroke prevention options.

• Disease risk prediction. Dr. Zhang has leveraged different machine learning and deep learning approaches to predict disease incidence for patients and further stratify patients into subgroups with different disease trajectories. These approaches have been used to predict disease risks and treatment outcomes.

Significance to patient care

Dr. Zhang's work aims to improve patient care outcomes by developing and applying novel predictive and causal machine learning techniques to help physicians intervene earlier and make personalized treatment plans.