Decisive differences in healthcare AIWhen decisions about your healthcare are informed by AI, bias in machine learning can have dire consequences. Ph.D. student Trenton Chang researches how inequities in healthcare delivery impact machine learning and AI.
Open-source patient model tops industry standardTested without needing hospitals to share data, the method for developing the model could speed further improvements in medical prediction tools
$1.1M grant supports learning more about early Alzheimer's with machine learningData from patient records could provide a valuable historical perspective on which factors increase Alzheimer's risk.
Seven papers by CSE researchers presented at AAAI 2021
Twelve students and faculty co-authored papers spanning several key application areas for AI.
Precision health in the palm of your hand
Recent breakthrough developments in technologies for real-time genome sequencing, analysis, and diagnosis are poised to deliver a new standard of personalized care.
Faster than COVID: a computer model that predicts the disease’s next move
Predictive model could help care providers stay safe, anticipate patient needs.
Computer scientists employ AI to help address COVID-19 challenges
Five multidisciplinary research teams are working on projects to assist with the coronavirus outbreak and to help find solutions to pressing problems.
Jenna Wiens recognized with Sloan Research Fellowship
She was recognized for her work harnessing patient data to improve healthcare outcomes.
2020 EECS Outstanding Achievement AwardsEECS honors four faculty members for their outstanding accomplishments to the community.
Michigan AI celebrates second annual symposium
The goal of the symposium is to facilitate conversations between AI practitioners from Michigan and beyond.
Taking machine-learning models in health care from concept to bedsideThe authors provide an overview of common challenges to implementing ML in a health-care setting, and describe the necessity of breaking down the silos in ML.
Jenna Wiens Named New Precision Health Co-Director
Wiens is transitioning to Co-Director from a successful role as a Co-Lead for Precision Health’s Data Analytics & IT Workgroup, which expanded access to data and research tools across the university.
Two papers announced among 10 most influential in healthcare and infection control
The papers provide data-driven solutions to hospital infection and the use of machine learning in healthcare.
Preventing deadly hospital infections with machine learning
Model successfully applied to data from medical centers with different patient populations, electronic health record systems
Jenna Wiens named Morris Wellman Faculty Development Professor
This professorship is awarded to junior faculty members in CSE in recognition of outstanding contributions to teaching and research.
CS kickStart wants first-year women to succeed in computer science
CS KickStart is a free week long summer program for incoming first-year students that aims to improve the enrollment and persistence of women in U-M’s computer science program.
Precision health pioneer named to MIT Technology Review innovator list
The national magazine recognized Jenna Wiens as one of 2017’s 35 Innovators Under 35.
U-M researchers launch fight against C. difficile with $9.2M grant from NIH
Prof. Wiens will continue to use machine learning techniques to study the disease.
Machine learning proves useful for analyzing NBA ball screen defense
The team used machine learning to extract information from NBA sports data for automatically recognizing common defense strategies to ball screens.
Jenna Wiens receives NSF CAREER Award to increase the utility of machine learning in clinical care
Her primary research interests lie at the intersection of machine learning and healthcare.