In today’s economy, many workers have transitioned from manual labor toward knowledge work, a move driven primarily by technological advances, and workers in this domain face challenges around managing non-routine work, which is inherently uncertain. Automated interventions can help workers understand their work and boost performance and trust. In a new study, researchers explored how artificial intelligence (AI) can enhance performance and trust in knowledge work environments.

Individuals with generalized anxiety disorder (GAD), a condition characterized by daily excessive worry lasting at least six months, have a high relapse rate even after receiving treatment. Artificial intelligence (AI) models may help clinicians identify factors to predict long-term recovery and better personalize patient treatment, according to researchers from Penn State.

At the height of the COVID-19 pandemic, hospitals frequently ran short of beds in intensive care units. But even earlier, ICUs faced challenges in keeping beds available. With an aging American population, 11% of hospital stays included ICU stays.

Artificial intelligence (AI) offers a possible solution, says Indranil Bardhan, professor of information, risk, and operations management and Charles and Elizabeth Prothro Regents Chair in Health Care Management at Texas McCombs.

AFib (short for atrial fibrillation), a common heart rhythm disorder in adults, can have disastrous consequences including life-threatening blood clots and stroke if left undetected or untreated. A new study demonstrates that UNAFIED, a highly accurate artificial intelligence (AI) prediction model which uses machine learning to parse information acquired from a patient's electronic health record (EHR) to predict whether a patient has or might develop detectable AFib

Low-value care - medical tests and procedures that provide little to no benefit to patients - contributes to excess medical spending and both direct and cascading harms to patients. A research team from Mass General Brigham and their collaborators have found that telemedicine may help to reduce the use of low-value tests. The work is published in JAMA Internal Medicine.

Imagine walking into a supermarket, train station, or shopping mall and having your eyes screened for glaucoma within seconds - no appointment needed. With the AI-based Glaucoma Screening (AI-GS) network, this vision could soon become a reality.

Glaucoma is the leading cause of irreversible blindness in Japan and worldwide. Early detection is critical, as the disease progresses silently, slowly constricting one's peripheral field of vision.

Researchers have developed an artificial intelligence (AI) approach that accelerates the identification of genes that contribute to neurodevelopmental conditions such as autism spectrum disorder, epilepsy and developmental delay. This new powerful computational tool can help fully characterize the genetic landscape of neurodevelopmental disorders, which is key to making accurate molecular diagnosis, elucidating disease mechanism and developing targeted therapies.