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

Their study is centred around answering three research questions: Do ANNs perform better than the traditional multiple regression models in the prediction of lighting parameters and energy demand of ...

Explore how artificial intelligence and digital innovations are transforming sludge dewatering in wastewater systems, ...

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

Medical device makers use AI to turn EU regulatory challenges into competitive advantages via supply chain optimization.

For Medicaid care management, focusing on rising-risk patients is more effective than targeting high-cost claimants, whose spending tends to decrease over time due to regression to the mean.

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 ...

The AI products that succeed are rarely "moonshots." Success comes from a systematic framework that pairs business metrics ...

This course provides a foundational understanding of machine learning, data analysis, and algorithm development ... Students ...

The rushed and uneven rollout of A.I. has created a fog in which it is tempting to conclude that there is nothing to see here ...