Machine learning model predicts fall risk for lower limb amputees with up to 80% accuracy, with implications for future smartphone apps

Researchers identify three types of post-amputation pain: phantom limb pain, residual limb pain, and musculoskeletal pain, which behave differently and require personalized care. The study's findings suggest that prosthetic design can directly influence comfort during real-world movement, improving mobility and quality of life for indi...

A study by Osaka Metropolitan University found that upper limb exercise testing underestimated cardiopulmonary function, indicating it cannot substitute cycle ergometers. Researchers call for further research to clarify factors affecting the relationship between heart rate and oxygen uptake during exercise.

Researchers at San Francisco State University have developed a step-by-step machine learning tutorial to detect antibiotic resistance in patients. The team used a publicly available dataset to train four popular machine learning models, which can be easily accessed through Google Colab. The tutorial aims to make machine learning access...

Scientists unveiled a spatial cell atlas of the entire developing human limb, capturing intricate processes governing rapid development. The study uncovers new links between developmental cells and congenital limb syndromes, such as short fingers and extra digits.

A machine learning model accurately predicted no-shows and late cancellations in primary care practices, with the gradient boost model achieving 85% accuracy for no-shows and 92% for late cancellations. Patient characteristics such as sex, age, and socioeconomic status played a significant role in missed appointments.

A new study reveals concerning regional disparities in lower limb amputations caused by peripheral arterial disease, with the North of England experiencing the highest rates. The study highlights the urgent need to improve care and prevention strategies, particularly for people with diabetes.