Predicting Fall Risks in Older Adults with Depression: A Machine Learning Approach - Ep 183

Predicting Fall Risks in Older Adults with Depression: A Machine Learning Approach - Ep 183

From ACCP JOURNALS by ACCP JOURNALS

May 19, 2026 · 30 min

About this episode

Dr. Ryan Carnahan interviews Dr. Jenny Lo-Ciganic about using machine learning to predict fall-related injuries in older adults with depression.

Dr. Ryan Carnahan, Pharmacotherapy's statistical scientific editor, interviews Dr. Jenny Lo-Ciganic about her research on the use of machine learning models to predict fall-related injuries among older adults with depression. Lo-Ciganic describes her work using real-world data and advanced analytics to improve medication safety and decision support. The discussion reviews the burden of falls and how depression increases risk, noting prior antidepressant–fall associations may reflect confounding by indication. They also address key injurious fall predictors, including frailty, age, prior falls, osteoarthritis, antidepressant dose, and regional social/health measures. Read the full manuscript at: https://accpjournals.onlinelibrary.wiley.com/doi/ftr/10.1002/phar.70087 .

People in this episode

Host: Dr. Ryan Carnahan

Guest: Dr. Jenny Lo-Ciganic

Topics covered

  • fall risks
  • older adults
  • depression
  • machine learning
  • medication safety
  • injurious falls

Keywords

  • fall prediction
  • older adults
  • depression
  • machine learning
  • medication safety
  • injurious falls
  • antidepressants

Mentioned in this episode

Organizations: Pharmacotherapy, ACCP

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