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 ...

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

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

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

Objectives Disease activity assessment is important for Crohn’s disease (CD) management, since it involves the initial and subsequent therapeutic schedule. The purpose of this study is to identify a ...

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.

A quality improvement initiative in a hepatology clinic increased alcohol use disorder pharmacotherapy prescriptions from 10% ...

The method will be a combination of a number of ML algorithms, and the method will give new opportunities ... Real-life models, e.g., logistic regression, K-nearest neighbors, decision trees, random ...

These questions come from my Udemy training and the certificationexams.pro website, resources that have helped many students pass the DP-100 certification. These are not DP-100 exam dumps or ...

The authors used a Bayesian modeling framework to fit behavior and serotonin neuron activity to reward history across multiple timescales. A key goal was to distinguish value coding from other ...