Researchers from IRTA and IrsiCaixa, partners in the EPIVINF project, have identified the golden Syrian hamster as a potential relevant model for studying the biology of long COVID, also known as post-COVID-19 condition (PCC).

Long COVID is not a single disease but a complex syndrome involving a range of persistent symptoms. People suffering from it report overwhelming fatigue, memory lapses, "brain fog,"

University of Arizona researchers in the Gutruf Lab have developed a comfortable, easy-to-use wearable device that incorporates artificial intelligence (AI) to detect subtle warning signs of frailty, signifying a leap forward in elderly care.

"The current model of care is lagging behind," said Philipp Gutruf, associate department head of biomedical engineering and senior author on the study.

Artificial intelligence (AI) may be able to reveal how fast your body is aging by analyzing a chest X-ray, according to a new study published in The Journals of Gerontology. Researchers found that a deep learning model was able to detect subtle, age-related changes in the heart, lungs, and overall health more effectively than leading DNA-based "epigenetic clocks."

Pathology has long been the cornerstone of cancer diagnosis and treatment. A pathologist carefully examines an ultrathin slice of human tissue under a microscope for clues that indicate the presence, type, and stage of cancer.

To a human expert, looking at a swirly pink tissue sample studded with purple cells is akin to grading an exam without a name on it - the slide reveals essential information about the disease without providing other details about the patient.

Researchers at the University of Pennsylvania have launched Observer, the first multimodal medical dataset to capture anonymized, real-time interactions between patients and clinicians. Much like the medical drama The Pitt, which portrays life in the emergency room, Observer lets outsiders peer inside primary care clinics - only, in this case, none of the filmed interactions are fictional.

Lung infections like pneumonia are among the world’s top killers - but diagnosing them is notoriously hard.

Now, researchers at UC San Francisco have found a way to identify these infections in critically ill patients by pairing a generative AI analysis of medical records with a biomarker of lower respiratory infections.

Scientists at the Icahn School of Medicine at Mount Sinai have developed a novel artificial intelligence (AI) tool that not only identifies disease-causing genetic mutations but also predicts the type of disease those mutations may trigger.

The method, called V2P (Variant to Phenotype), is designed to accelerate genetic diagnostics and aid in the discovery of new treatments for complex and rare diseases.