Through our Challenge Initiatives, the Center for Data-Intensive Health Science Research at MIDAS is funding three initial projects in data science methodology development and application. “Michigan Center for Single-Cell Genomic Data Analytics”, led by Jun Li of the U-M Medical School, will develop state-of-the-art methodologies in single-cell genomics that can be applied to a large number of research fields in biology. “From Big Data to Vital Insights: Michigan Center for Health Analytics & Medical Prediction (M-CHAMP),” led by Brahmajee K. Nallamothu of the U-M Medical School, will develop innovative analytic techniques to examine temporal patterns in complex patient data to improve the early diagnosis and treatment of a variety of health conditions. “Identifying Real-Time Data Predictors of Stress and Depression Using Mobile Technology”, led by Srijan Sen of the U-M Medical School, will utilize multi-modal mobile and wearable data to develop personalized models of depression onset under stress by examining the interactions of physiology, behavior and environment.
With these projects as the initial core research, the Center for Data-Intensive Health Science Research will focus on:
- Disseminating tools and methods, as soon as they become available, to empower campus-wide health research that integrates data science.
- Building a collaborative network of Big Data health researchers that will propel UM to the forefront of data-intensive health research in the nation.
- Forming industry partnerships and transform research findings into clinical applications that have immediate impact on healthcare.
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