I am a computational biologist interested in interpretable machine learning for genomics and health care. Interpretable ...

Article Title Genetic and therapeutic landscapes in cohort of pancreatic adenocarcinomas: next-generation sequencing and machine learning for full tumor exome analysis ...

Genetic Subgroups of Follicular Lymphoma Can Be Distinguished by Machine Learning —Researchers recently identified 2 distinct genetic subgroups in follicular lymphoma, shedding light on the ...

A team of Johns Hopkins biomedical engineers has developed a machine-learning model that can predict which enhancers play a role in normal development and disease—an innovation that could someday ...

Novel machine learning method can improve genetic risk assessments for non-white populations Researchers have developed a scalable AI-based approach that makes use of genetic studies that include ...

University of Minnesota Twin Cities researchers have constructed a robot that uses machine learning to fully automate a complicated microinjection process used in genetic research.

A study by researchers from the University of Sheffield and Stanford University School of Medicine demonstrates how a new machine learning model for the discovery of genetic risk factors for ...

A groundbreaking study led by USC Assistant Professor of Computer Science Ruishan Liu has uncovered how specific genetic mutations influence cancer treatment outcomes-insights that could help ...

Layered within these actions are additional information, such as gait pattern, velocity, distance traveled and locations visited. Using machine learning, they evaluated this information and identified ...