Computationally modeling the hot spots
Poised to make a difference
Exceptional computational detective work has the potential to reshape our understanding of when and why diseases strike
Applying deep learning to biomedical images has the potential to enable earlier and more accurate disease detection, allow more precisely tailored treatment plans, and ultimately improve patient outcomes.
Computation strives to make prostate cancer less menacing
To understand biology—and provide appropriate medical care—scientists need to understand interactions across multiple scales. Hence the Physiome.
Simulations can teach us how young bodies and faces develop; how an artery compensates for decades of fatty plaque deposits by growing and thickening its walls; how tissue engineers can best coax endothelial cells to develop into organized sheets of skin for burn patients; and how cancerous tumors invade neighboring tissue.
Biomarker research, genetics, and imaging are all coming into play
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