Integration of Palliative Care into Heart Failure Care: Consensus-Based Recommendations from HFSA Out Now!
Andrew Delgado, PhD headshot

Andrew Delgado, PhD


Assistant Professor
Center of Biostatistics, Department of Population Health Science and Policy
Icahn School of Medicine at Mount Sinai

Dr. Andrew Delgado is an Assistant Professor at the Center of Biostatistics in the Department of Population Health Science and Policy at the Icahn School of Medicine at Mount Sinai. His expertise centers on the statistical analysis of complex healthcare data and collaboration across interdisciplinary teams. Dr. Delgado’s research primarily focuses on improving clinical outcomes and understanding in rehabilitation medicine, especially in the contexts of spinal cord injury and chronic pain management. Previously, Dr. Delgado contributed significantly as a clinical statistician at Mount Sinai’s Department of Rehabilitation Medicine and Human Performance, where he collaborated on study design and development of statistical analysis plans for pioneering biotechnologies and analyzed data for innovative healthcare solutions. His early career work included pilot studies on the use of exoskeleton technologies in acute spinal cord injury rehabilitation. As an active member of the American Congress of Rehabilitation Medicine, Dr. Delgado serves on the executive committees for both the Measurement and Spinal Cord Injury special interest groups. More recently, Dr. Delgado has started the task force working group titled, ‘Measurement Innovations: Integrating Machine Learning and Digital Technologies in Rehabilitation,’ which is seeking to improve research design and data analysis practices in rehabilitation sciences. Presently, Dr. Delgado is collaborating on several projects which include mechanistic studies for ketamine and psilocybin in the treatment of depression with and without mild cognitive impairment, the prediction of depression status and severity using novel app-based technologies, machine learning to predict childhood allergy via blood-based biomarkers, and autonomic function for both spinal cord injury and multiple sclerosis.