A new tactile sensing carpet from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) can estimate human poses without using cameras, in a step towards  improving self-powered personalized healthcare, smart homes, and gaming.

The confluence of medicine and artificial intelligence stands to create truly high-performance, specialized care for patients, with enhanced precision diagnosis and personalized disease management.

MIT researchers have generated what they describe as the most accurate and complete gene annotation of the SARS-CoV-2 genome. In their study, which appears today in Nature Communications, they confirmed several protein-coding genes and found that a few others that had been suggested as genes do not code for any proteins.

Improper adherence to doctors’ orders is commonplace, accounting for thousands of deaths and billions of dollars in medical costs annually. MIT researchers have developed a system to reduce those numbers for some types of medications.

A study from MIT shows how coronavirus skeptics have marshalled data visualizations online to argue against public health orthodoxy about the benefits of mask mandates. Such “counter-visualizations” are often quite sophisticated, using datasets from official sources and state-of-the-art visualization methods.

Researchers develop a system to identify drugs that might be repurposed to fight the coronavirus in elderly patients.

A team of scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Jameel Clinic (J-Clinic) demonstrated a deep learning system to predict cancer risk using just a patient’s mammogram. The model showed significant promise and even improved inclusivity: It was equally accurate for both white and Black women, which is especially important given that Black women are 43 percent more likely to die from breast cancer.