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 ...

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 ...

A new risk prediction model shows good predictive value in identifying risk for neurogenic bladder (NB) after spinal cord injury (SCI) and guiding clinical interventions, according to a study ...

This course covers nonparametric modeling of complex, nonlinear predictive relationships in data with categorical (classification) and numerical (regression) response variables. Supervised learning ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Patients are less comfortable with predictive models used for health care administration compared with those used in clinical practice, signaling misalignment between patient comfort, policy, and ...

Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...

Patient-reported outcome measures and clinical scales were ineffective in predicting responses to full-agonist opioids for chronic pain.

Companies such as Google, Facebook and Amazon.com understand this lesson well, which is why you start seeing ads for products that you’ve looked at online about five seconds after you browsed for them ...

If you scan the ad tech headlines, you’d assume artificial intelligence (AI) offers the solution to every challenge facing today’s brands and agencies. Even if marketers understand how the hype ...