Machine learning model improves transplant risk assessment for patients with myelofibrosis, helping clinicians make informed decisions, as per an expert. A new machine learning model has significantly ...
My company, Kickfurther, has carved out a niche by connecting businesses in need of funding for their retail inventory with buyers of that inventory. A key component of this business model is the ...
A total of 590 patients were identified, 432 in the development set and 158 in the validation set. The median age was 51 years, and 55.8% (329 of 590) experienced grade 3 or 4 toxicity. The ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...
Systemic sclerosis (SSc) is a severe autoimmune disease with complex genetic causes. Some genetic contributors have been identified, but others remain unknown, which has impeded development of ...
Please provide your email address to receive an email when new articles are posted on . Researchers are using machine learning to identify data-driven PCOS subtypes. Findings may lead to more precise ...
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