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 ...

A study of 1,099 patients was conducted to test decision tree-based learning algorithms to predict analgesic consumption and patient-controlled anesthesia control readjustment, according to 7thSpace.

Decision trees are among the more popular applications of machine learning in the capital markets. Uses include finding patterns in request-for-quote (RFQ) datasets and predicting stock prices.

Low-dose computed tomography (LDCT) screening is effective in reducing lung cancer mortality by detecting the disease at earlier, more treatable stages. However, high false-positive rates and the ...

Randomized Trial of Fixed-Dose Capecitabine Compared With Standard-Dose Capecitabine in Metastatic Breast Cancer: X-7/7 Trial Data were obtained from the Northwell Health cancer registry for patients ...

This course addresses the application of data recorded from models, simulation or measurements for prediction, inference of estimation of system behavior. Students are introduced to AI/machine ...

The Annals of Statistics, Vol. 49, No. 5 (October 2021), pp. 2531-2551 (21 pages) Proposed by Donoho (Ann. Statist. 25 (1997) 1870–1911), Dyadic CART is a nonparametric regression method which ...

Executives are inviting geographers into the boardroom. Why? Together, they are answering some of the most complex climate-risk questions: · Where are the greatest threats to buildings and other ...

A cardiovascular disease (CVD) risk prediction tool developed by Northwestern Medicine scientists may also be effective for identifying which patients would most benefit from statin therapy, according ...