Many scientific problems entail labeling data items with one of a given, finite set of classes based on features of the data items. For example, oncologists classify tumors as different known cancer ...

The vehicles on American roads have grown larger — and they are killing thousands more pedestrians, a Times investigation ...

Objective Unlike several other fields of healthcare, little is known about the size of ‘therapist effects’ on patient ...

Objectives To assess the outcomes of patients undergoing open abdominal surgery at a National Referral Hospital in Tanzania. Design A prospective, observational, single-arm cohort study. Setting Dar ...

Background Understanding the ‘real-world’ challenges of delivery of pre-exposure prophylaxis (PrEP) among men who have sex ...

Objectives To examine primary care contacts among individuals with eating disorders (EDs) and assess differences across ...

Missing a night of sleep leaves a specific chemical signature in saliva that can be reliably detected with a high degree of ...

Abstract: Class imbalance is a persistent challenge in machine learning, particularly in high-stakes applications such as medical diagnostics, bioinformatics, and fraud detection, where the minority ...

Abstract: Medical datasets are usually imbalanced, where negative cases severely outnumber positive cases. Therefore, it is essential to deal with this data skew problem when training machine learning ...

Low energy availability (EA) is suspected to be the underlying cause of both the Female Athlete Triad and the more recently defined syndrome, Relative Energy Deficiency in Sport (RED-S). The ...

This project predicts whether a passenger survived the Titanic disaster using supervised machine learning techniques. The problem is treated as a binary classification task where the target variable ...