Digital Health and Life Sciences Informatics have entered an era of major data transformation spurred by the use of advanced analytics and related technologies. Data-driven translational research, population health management, and precision medicine have served as the catalysts for this transformation.

With access to massive amounts of structured and unstructured patient data across a wide range of data sources, data science can aid in diagnosing patient conditions, developing new therapeutics, matching treatment with best outcomes, and predicting patients’ risk levels for disease. In a “learning healthcare system” like the University of Miami, the availability of millions of patient records means that predictive analytics can identify comparable physical symptoms in patients who are the same age, gender, ethnicity, and who display similar responses to a specific medication. By analyzing vast data sets across different systems, data science can inform healthcare decisions and transform basic and translational biomedical research. Furthermore, cutting-edge data science can also be used to understand and predict marine ecosystems and their use in the discovery of new drugs.

Combining the most impressive academic programs with one of the most extensive health care systems in all of south Florida, the University of Miami is well positioned to harness the power of patient-record data science.

IDSC Digital Health and Life Sciences Informatics encompasses Drug Discovery, Population Health Informatics, and Social and Behavioral Data Science.

Stephan Schürer, PhD Director, IDSC Drug Discovery

Azizi Seixas, PhD Director, IDSC Population Health Informatics

Daniel Messinger, PhD Director, IDSC Social and Behavioral Data Science

Experts

Recent Publications Do-It-Yourself Diabetes Management: Perspectives of a Patient, a Physician, and an Ethicist Ethics in Biomedical and Health Informatics: Users, Standards, and Outcomes Generating Realistic COVID-19 X-rays with a Mean Teacher + Transfer Learning GAN Deep Learning Based Multimedia Data Mining for Autism Spectrum Disorder (ASD) Diagnosis Commercial Interests in Continuing Medical Education: Where Do EHR Vendors Fit? The Clinical Kinase Index: Prioritizing Understudied Kinases at Targets for the Treatment of Cancer Yearbook of Medical Informatics: Ethics in Health Informatics Computational Identification of Kinases That Control Axon Growth in Mouse Inference From Complex Networks: Role of Symmetry and Applicability to Images Bioethics and Precision Medicine Focus on Information Technology piNET: A Versatile Web Platform for Downstream Analysis and Visualization of Proteomics Data Frontiers Editorial on Research Topic: Trends in Digital Medicine Balancing Risks and Benefits of Artificial Intelligence in the Health Sector Imprecise Data and Their Impact on Translational Research in Medicine FAIR SCI Ahead: The Evolution of the Open Data Commons for Pre-Clinical Spinal Cord Injury Research From Medical Imaging to Radiomics: Role of Data Science for Advancing Precision Health Identification of DOT1L Inhibitors by Structure-Based Virtual Screening Adapted from a Nucleoside-Focused Library Protemic Cellular Signatures of Kinase Inhibitor-Induced Cardiotoxicity: Mount Sinai DToxS LINCS Center Dataset Interventional Treatment of Incomplete Seal After Transcatheter or Surgical Left Atrial Appendage Closure Role of Complex Networks for Integrating Medical Images and Radiomic Features of Intracranial Ependymoma Patients in Response to Proton Radiotherapy