Optometry Advisor

Multiple Alternatives in Alerts Boost Likelihood of New Care Choices

In a randomized clinical trial, researchers compared the effect of single vs multiple treatment alternatives on care ...
Journal of Medical Internet Research

Longitudinal Model Shifts of Machine Learning–Based Clinical Risk Prediction Models: Evaluation Study of Multiple Use Cases Across Different Hospitals

Objective: This study aimed to assess the impact of a model shift on ML-based prediction models by evaluating 3 different use cases—delirium, sepsis, and acute kidney injury (AKI)—from 2 hospitals (M ...
Open Heart

Machine learning-based cardiovascular risk calculator for non-cardiac surgery

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
IEEE

Gender Classification Using K-Nearest Neighbors and Logistic Regression Models

Abstract: This work provides a hybrid model for gender identification integrating face features with logistic regression with K-Nearest Neighbors. The model reached an amazing accuracy of 96% with a ...
thorax.bmj

Development and validation of PRECISE-X model: predicting first severe exacerbation in COPD

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...
IEEE

Prediction of Employee Attrition Classification and Retention Strategies Using Gradient Boosting with Binary Logistic Regression

Abstract: A voluntary or involuntary parting of an employee from an organization is known as and the strategies to maintain an employee are known as Employee attrition (turnover) and retention.
GitHub

MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Models

After downloading the WSIs, please use the CLAM repository to pre-process the WSIs and extract the features. The features should be put into the ./data directory. Then, use the h5toPyG.ipynb notebook ...