Researchers at Massachusetts General Hospital (MGH) have developed a deep learning model that identifies imaging biomarkers on screening mammograms to predict a patient’s risk for developing breast cancer with greater accuracy than traditional risk assessment tools. Results of the study are being presented at the annual meeting of the Radiological Society of North America (RSNA). […]
Novel deep learning method enables clinic-ready automated screening for diabetes-related eye disease
Researchers at Helmholtz Zentrum München together with LMU University Eye Hospital Munich and the Technical University of Munich (TUM) created a novel deep learning method that makes automated screenings for eye diseases such as diabetic retinopathy more efficient. Reducing the amount of expensive annotated image data that is required for the training of the algorithm, […]
Data science pathway prepares radiology residents for machine learning
A recently developed data science pathway for fourth-year radiology residents will help prepare the next generation of radiologists to lead the way into the era of artificial intelligence and machine learning (AI-ML), according to a special report published in Radiology: Artificial Intelligence. AI-ML has the potential to transform medicine by delivering better and more efficient […]
Additional data, advanced analytics improve performance of machine learning referral app
Research scientists from Regenstrief Institute and Indiana University have further improved the performance of Uppstroms, a machine learning application that identifies patients who may need referrals to wraparound services, by incorporating additional personal and population-level data sources and advanced analytical approaches. Research team affiliations include Regenstrief, IU Fairbanks School of Public Health at IUPUI, IU […]
Nudges combined with machine learning triples advanced care conversations among patients with cancer
An electronic nudge to clinicians—triggered by an algorithm that used machine learning methods to flag patients with cancer who would most benefit from a conversation around end-of-life goals—tripled the rate of those discussions, according to a new prospective, randomized study of nearly 15,000 patients from Penn Medicine and published today in JAMA Oncology. Early and […]
Anticipating heart failure with machine learning
Every year, roughly one out of eight U.S. deaths is caused at least in part by heart failure. One of acute heart failure’s most common warning signs is excess fluid in the lungs, a condition known as pulmonary edema. A patient’s exact level of excess fluid often dictates the doctor’s course of action, but making […]
A science teacher explains: Water has baffling properties
Water can move against the force of gravity as seen in capillary action in plants and our blood vessels, can stick together making its surface act like a stretched membrane by virtue of its property of surface tension enabling small insects to walk on it. By Rachna Arora Life can exist without sunlight, even oxygen, […]
Using COVID-19 patient data to train machine learning models for healthcare
One short week ago, I called on governments to use existing data and proven machine learning and AI techniques to help healthcare systems combat the COVID-19 pandemic. The response was amazing. My team and I received encouragement, ideas, and proposals for collaboration. We also received, courtesy of Public Health England, a set of (depersonalized) data […]
Learning from echoes of past plagues, poxes, flus
Millions of people confine themselves to their homes as they battle an invisible, viral enemy. Schools and theaters close. Playgrounds empty. Medical staff choose which patients will get life-saving respirators, and which will not. That was polio at its North American peak in the early 1950s. Today, the worldwide COVID-19 outbreak is both familiar and […]