AI & Society, states that algorithmic systems often construct competing but equally valid “model-worlds,” offering empirical support for a philosophical claim that evidence alone cannot uniquely ...

A recent study on the development and validation of an AI-based framework for first-trimester preeclampsia risk assessment ...

Researchers sought to determine an effective approach to predict postembolization fever in patients undergoing TACE.

Background and objectives Lung cancer remains the leading cause of cancer-related mortality worldwide. Early detection of pulmonary nodules is crucial for timely diagnosis and effective treatment.

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

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

Researchers have significantly enhanced an artificial intelligence tool used to rapidly detect bacterial contamination in food by eliminating misclassifications of food debris that looks like bacteria ...

Objectives Since 1985, the international healthcare community has recommended the ideal rate of caesarean section (CS) to be 10%–15% at the national level. The literature has reported that overused CS ...

Objectives To describe the incidence, presentation and long-term health outcomes of suicidal thoughts and behaviours (STBs) in children aged 12 years or under. Methods This population-based study ...

Background Approximately one in three patients with acute ischemic stroke (AIS) suffer from a premorbid disability prior to ...

Li and colleagues developed a deep-learning model to analyze EEG recordings and detect event-level EEG spikes. 2. The model achieved high accuracy and a low false-positive rate, with only 32% of human ...