Our lab was honored to receive a grant from the Alzheimer’s Association for the diligent work in trying to uncover the mechanisms of Alzheimer’s disease. We are very proud to receive this grant and aim to continue making progress on this front. Check out the BME department press release for more information!
Congratulations to Nishad Khamankar, the first author of the highly anticipated bi-level positive airway pressure (Bi-PAP) for ALS. This paper was published in Frontiers in Neurology and examines the benefits of daily Bi-PAP and cough assist on the survival of ALS patients. This paper has helped move ALS care forward and our lab is very proud of Nishad for his work.
Download your copy here: https://www.frontiersin.org/articles/10.3389/fneur.2018.00578/full
Congratulations to all of our lab members who had abstracts accepted for poster presentations at the Fall 2018 BMES Conference.
Special congratulations to the Bi-PAP team for being selected for to give an oral presentation!
- Biocuration: Improving Automation, Productivity, Accuracy and Quality Control
- Authors: Joseph Murphy, Kathleen Jordan, Andrew Sedler, Keelie Denson, Cassie Mitchell
- Systematic Analysis of the Topic Landscape of Aging and Alzheimer’s Disease Literature
- Authors: Andrew Sedler, Cassie Mitchell
- Dynamic Meta-Analysis Approach to In Silico Models of Temporal Multi-scalar Neurophysiology
- Authors: Albert Lee, Stefano Travaglino, Cassie Mitchell
- Informatics-based Literature Mapping to Expedite Research for Chronic Myeloid Leukemia
- Authors: Nidhi Mehra, Andrew Sedler, Cassie Mitchell
- Optimizing PEG “Feeding Tube” Intervention for ALS using Predictive Medicine
- Authors: Leila Bond, Paulamy Ganguly, Nishad Khamankar, Nolan Mallet, Cassie Mitchell
- Optimizing Bi-PAP Intervention for ALS using Predictive Medicine
- Authors: Nishad Khamankar, Leila Bond, Paulamy Ganguly, Nolan Mallet, Cassie Mitchell
This is the long awaited Pfohl 2018 et. al. article in Frontiers in Neuroinformatics, which used a machine learning model to predict and classify ALS clinical survival. This paper showcases where our lab is headed in terms of potential complexity and machine learning approaches to predictive medicine.
This paper has an amazing string of successful co-authors who were all undergrad alums in the lab. Stephen Pfohl is now an NSF fellow getting a PhD in Bioinformatics at Stanford, Renaid Kim is getting an MD-PhD at University of Michigan Medical Scientist Training Program, and Grant Coan is getting his MD at University of Texas at San Antonio.