Health Care
Three Papers Detail New Computational Models to Predict Severe Illness from COVID-19
Data Science and AI Methods Offer Predictive Systems to Aid Healthcare Policy Management and Level-of-Care Requirements Data science and AI methods have evolved to become a powerful tool in developing strong predictive models to help improve our understanding and treatment of COVID-19. “Given ample data, and assuming that the future is not completely random (like […]
New COVID-19 research focuses on Latin America
Informing Policy, Resource Allocation and Workplace Adjustment Policies COVID-19 has taken the world by storm, placing significant pressures on healthcare systems. Particularly in countries with limited testing resources and capacity-constrained health care systems, it is essential to determine who is at most risk for developing COVID-19. Knowing who may or may not need medical attention, and […]
A Soft Robotic Sleeve to Enable Safer and Easier Colonoscopy Procedures
Current flexible endoscopes have limited dexterity and sensor feedback, making navigation in colonoscopy a challenging task. These technical limitations make screening procedures poorly tolerated by patients, leading to low rates of compliance with screening guidelines and/or incomplete colonoscopy, that is associated with higher rates of interval proximal colon cancer. Alternative engineering solutions have been proposed […]
A Soft Robotic Sleeve to Enable Safer and Easier Colonoscopy Procedures
Current flexible endoscopes have limited dexterity and sensor feedback, making navigation in colonoscopy a challenging task. These technical limitations make screening procedures poorly tolerated by patients, leading to low rates of compliance with screening guidelines and/or incomplete colonoscopy, that is associated with higher rates of interval proximal colon cancer. Alternative engineering solutions have been proposed […]
AI in Medicine Advances with BU-MIT Research Team
Researchers from Boston University and the Massachusetts Institute of Technology have pioneered an AI method that learns from existing data how to make specific recommendations (“prescriptions”) to optimize a certain outcome. Their research findings have been published in this month in PLOS ONE. The paper titled “Prescriptive Analytics for Reducing 30-day Hospital Readmissions after General Surgery” […]
POV: COVID-19 Shows Us We Need Rapid Response Data Science Teams
Eric Kolaczyk, Director of Hariri Institute of Computing and Faculty Affiliate of CISE, contributed an opinion piece published by BU Today on June 4th entitled “POV: COVID-19 Shows Us We Need Rapid Response Data Science Teams.” In it, Professor Kolacyzk describes how the COVID-19 pandemic is not only an indication of the need for development but also a rapid response […]
Yazicigil on Track to Monitor the GI Tract
“This is an ingestible sensor that will track and record the inflammation of the GI tract in a continuous and minimally-invasive manner, and especially tailored toward an individualized response for each patient’s disease,” said Yazicigil. Yazicigil’s team in collaboration with MIT is currently developing a mm-scale ingestible micro-bio-electronic device by leveraging the natural advantages of […]
Secure Bio-Engineered Sensors for Disease Management
The objective of this project is to address the limitations in our current ability to measure disease biomarkers in the gastrointestinal tract. Unable to track the levels of these molecules, we have an incomplete picture of the process of inflammation, and thus cannot evaluate disease progression or how well treatments are working. To overcome gaps […]
BU-Harvard Team Wins $1.2M NSF Grant to Improve Women’s Reproductive Health using AI and Machine Learning
A multidisciplinary team of researchers from Boston University and Harvard University is working to address women’s reproductive health challenges with the help of a $1.2M, four-year grant funded by the National Science Foundation (NSF) through its Smart and Connected Health (SCH) program. The BU-led project will leverage machine learning and artificial intelligence to develop an […]
SCH: INT: Distributed Analytics for Enhancing Fertility in Families
The demands of modern life, education and career choices, as well as the availability of assisted reproductive technologies, are leading many individuals and couples to delay childbearing. This has contributed to infertility and sub-fertility emerging as significant public health problems in the U.S., affecting about 15% of couples, involving both men and women, and resulting […]