Machine learning predicts who will decline faster in Alzheimer’s disease using routine clinic data
Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
Relating brain activity to behavior is an ongoing aim of neuroimaging research as it would help scientists understand how the brain begets behavior — and perhaps open new opportunities for ...
PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...
This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...
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 ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
DataZapp brings AI and machine learning to deliver affordable, predictive demand generation and marketing data for home ...
A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a ...
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