AI for Health provides data-driven tools for healthcare:

  • Phenotype complex diseases.
  • Predict clinical outcomes and treatment effects.
  • Discover risk factors associated with clinical outcomes.
  • Support clinical decisions and precision medicine.

Research underway at Washington University in St. Louis

Wearable tech for contact tracing developed

Wearable tech for contact tracing developed

‘Potentially powerful’ automated tool could help fight COVID, future pandemics in hospitals

Interdisciplinary team wins award for paper on predicting postoperative complications with wearables, artificial intelligence

Interdisciplinary team wins award for paper on predicting postoperative complications with wearables, artificial intelligence

The award to Chenyang Lu and collaborators was announced at the UbiComp/ISWC 2023 conference

Artificial intelligence may assist decisions on which patients should get critical life support

Artificial intelligence may assist decisions on which patients should get critical life support

McKelvey Engineering, School of Medicine team develop machine-learning model using COVID-19 patient data

Learning physician burnout from electronic health record activities

Learning physician burnout from electronic health record activities

Interdisciplinary team develops deep learning model to predict burnout from electronic health record logs

Wearable fitness trackers help physicians track patient health

Wearable fitness trackers help physicians track patient health

Chenyang Lu applies machine learning, Internet of Things expertise to improve patient outcomes

Data from wearables could be a boon to mental health diagnosis

Data from wearables could be a boon to mental health diagnosis

Washington University team uses Fitbit data, deep learning to detect depression, anxiety

Personalized prediction of depression treatment outcomes with wearables

Personalized prediction of depression treatment outcomes with wearables

Interdisciplinary team builds multitask machine learning model for randomized controlled trial

Predicting surgical outcomes with machine learning

Predicting surgical outcomes with machine learning

Interdisciplinary team tackles complexity of clinical data in perioperative care

Early warning system model predicts deterioration of hospitalized cancer patients based on clinical data

Early warning system model predicts deterioration of hospitalized cancer patients based on clinical data

The model, developed in Chenyang Lu’s lab, may help warn of pending patient deterioration

Recent talks