MIT’s Dina Katabi has developed a non-contact, neural network-based system to detect Parkinson’s disease while a person is sleeping. By assessing nocturnal breathing patterns, the series of algorithms detects, and tracks the progression of, the disease —...
The US Army and USC Prof Maryam Shanechi have developed an algorithm that can determine which specific behaviors—like walking and breathing—belong to specific brain signals. Segmenting brain signals has been notoriously difficult, as all signals associated with...
DeepCOVID-XR is a Northwestern University developed algorithm that automatically detects the signs of COVID-19 on a basic X-ray of the lungs. The system is able to detect COVID-19 in X-rays 10 times faster than thoracic...
Sebastiano Massaro at the University of Surrey, Mihaela Porumb and Leandro Pecchia at the University of Warwick, and Ernesto Iadanza at the University of Florence have developed an advanced signal processing and machine learning method to...
CompCyst is a proof-of-concept study, led by Anne Marie Lennon at Johns Hopkins, which uses AI to more accurately determine which pancreatic cysts will become cancerous. The test evaluates molecular and clinical markers in cyst fluids,...
MIT CSAIL professor Regina Barzilayand Harvard/MGH professor Constance Lehman have developed a deep learning model that can predict breast cancer, from a mammogram, up to five years in the future. The model learned subtle breast tissue patterns that...
University of Vermont researchers have developed an algorithm that detects anxiety and depression in children’s voices with 80 per cent accuracy, according to a recent study. Standard diagnosis involves a 60-90 minute semi-structured interview with...
Xia Huiminand Guangzhou Women and Children’s Medical Center researchers used AI to read 1.36 million pediatric health records, and diagnosed disease as accurately as doctors, according to a recent study. Common childhood diseases were detected...
Lawson Health Research Institute, Mind Research Network and Brainnetome Center researchers have developed an algorithm that analyzes brain scans to classify illness in patients with complex mood disorders and help predict their response to medication....
Facebook and NYU’s fastMRIproject, led by Larry Zitnick, uses AI in an attempt to make MRI imaging 10 times faster. Neural networks will be trained to fill in missing or degraded parts of scans, turning...