By Hugo Francisco de Souza A new study shows that gut microbiome signatures, analyzed through advanced machine learning, can help identify individuals with more severe insulin resistance, offering ...

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...

Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...

City of Hope® Research Spotlight offers a glimpse into groundbreaking scientific and clinical discoveries advancing lifesaving cures for ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Familiar Super Bowl foes meet when the Seattle Seahawks battle the New England Patriots in the 2026 Super Bowl on Sunday, Feb. 8. Seattle advanced with a 31-27 win over the Los Angeles Rams in the NFC ...

As patients and employers look for alternatives to pricey GLP-1 drugs, Silicon Valley startup Twin Health is using AI and wearable sensors to help people make healthier choices. Rodney Buckley has ...