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 ...
An Dang, Special to The Denisonian Denison will debut a new minor in machine learning and artificial intelligence next semester. This program is designed to give students in technical fields a ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
And unlike traditional machine-learning, assisted-feature extraction in spectroscopy, the new method pinpoints phase transitions based on characteristic spectral features inside an energy gap, making ...
Using machine learning, an electronic nose can "smell" early signs of ovarian cancer in the blood. The method is precise and, ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
In the age of digital transformation, machine learning (ML) is rapidly becoming a pivotal technology in various sectors. One of its most exciting applications is in the field of advanced materials ...
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