Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...

A machine learning model using basic clinical data can predict PH risk, identifying key predictors like low hemoglobin and elevated NT-proBNP. Researchers have developed a machine learning model that ...

An analysis of 5 machine-learning algorithms identified predictors for moderate-to-severe cancer-related fatigue in patients with CRC undergoing chemotherapy.

Among adolescent girls with concussion, greater initial emotional symptom severity, reflected in higher anxiety, depression, and sleep disturbance scores, was associated with a higher likelihood of ...

The study’s AI-generated maps showed that the Locride area, located within the Aspromonte Geopark, faced the highest drought ...

Unlike conventional sustainability audits, which require time-consuming data collection and hardware deployment, this ...

Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...

Conclusions: There is a potential mismatch between what clinicians identify as important in determining palliative care need and final eligibility determinations. Patients with dementia were less ...

Older Canadian adults whose physicians prescribe first-generation antihistamines in the hospital are more likely to ...

Machine learning models estimated the probability of developing sepsis in children admitted to the emergency department.