When struggling to conceive, every second that ticks by feels precious. That makes it easy to get discouraged: 65 percent of those who seek fertility care eventually discontinue treatment, the majority due to stress. That's why Penn Medicine recently instituted a telemedicine-driven program aimed at seeing patients more quickly and starting treatments sooner.

Michigan State University (MSU) researchers are using big data and AI to identify current drugs that could be applied to treat new COVID-19 variants.

Finding new ways to treat the novel coronavirus and its ever-changing variants has been a challenge for researchers, especially when the traditional drug development and discovery process can take years.

The loss of any life can be devastating, but the loss of a life from suicide is especially tragic.

Around nine Australians take their own life each day, and it is the leading cause of death for Australians aged 15 - 44. Suicide attempts are more common, with some estimates stating that they occur up to 30 times as often as deaths.

Researchers at CeMM, the Medical University of Vienna (MedUni Vienna), and the Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases (LBI-RUD) joined efforts to use their expertise in machine learning and management of patients with cirrhosis to develop a non-invasive algorithm that can help clinicians to identify patients with cirrhosis at highest risk for severe complications.

By using artificial intelligence (AI), Houston Methodist researchers are able to predict hospitalization outcomes of geriatric patients with dementia on the first or second day of hospital admission. This early assessment of outcomes means more timely interventions, better care coordination, more judicious resource allocation, focused care management and timely treatment for these more vulnerable, high-risk patients.

Researchers at the University of Michigan Rogel Cancer Center have developed a computational platform that can predict new and specific metabolic targets in ovarian cancer, suggesting opportunities to develop personalized therapies for patients that are informed by the genetic makeup of their tumors. The study appeared in Nature Metabolism.

Members of the public are being asked to help remove biases based on race and other disadvantaged groups in artificial intelligence (AI) algorithms for healthcare.

Health researchers are calling for support to address how ‘minoritised’ groups, who are actively disadvantaged by social constructs, would not see future benefits from the use of AI in healthcare.