Dr. Michelle Hastings has RNA therapeutic being used to treat twins with ultra-rare form of Batten disease

Michelle Hastings
RNA therapeutic (developed by Dr. Michelle Hastings) is being used to treat twins with ultra-rare form of Batten disease. It'll be used to correct genes with specific mutations, like the CLN3 mutation responsible for the girls' disease. Read more here.

 
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Health Lab
How do you treat rotator-cuff tears?
Rotator-cuff tears appear most in adults over the age of 40. These injuries are typically treated with physical therapy and surgical intervention as a last resort.
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Health Lab Podcast
Do penile implants work for erectile dysfunction?
For people with erectile dysfunction, penile prosthesis surgery provides a safer, and more successful treatment option, than you might think.
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Dose of Reality
Seeing the Forest and the Trees: Rediscovering Forestry in Medical School
University of Michigan medical student Sahil Tolia shares his love of forestry, a pastime he was able to pursue as a first-year medical student thanks to the flexible schedule of preclinical year.
Girls Who Code executive board members
Department News
U-M Girls Who Code receive the Carol Hollenshead Inspire Award for Excellence in Promoting Equity and Social Change
The Carol Hollenshead Inspire Award for Excellence in Promoting Equity and Social Change recognizes faculty, staff and students — either an individual or a group — who have proven that social change is possible through persistent hard work and who demonstrate that one person can make a lasting difference in their communities. Girls Who Code was founded at U-M in 2017 by doctoral students in the Medical School’s Gilbert S. Omenn Department of Computational Medicine and Bioinformatics.
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Health Lab
Diagnostic stewardship optimizes detection of appendicitis
University of Michigan researchers found that emergency departments vary widely in how they balance the need to diagnose appendicitis with the potential harms of overtesting.
Yufeng Zhang, PhD
Department News
Yufeng Zhang, PhD, defended her bioinformatics dissertation thesis on machine learning models
Zhang's research focuses on developing data-driven identification and prediction systems for real-world medical applications. I am particularly interested in enhancing the generalization and interpretability of machine learning and deep learning models in medicine, as well as exploring innovative methods to improve model accuracy. To address challenges such as the lack of annotated data, limited generalization capabilities, and the need for interpretable models, I have applied several strategies, including privileged information learning, self-supervised learning, and approximate reasoning.