Philadelphia communities help AI machine learning get better at spotting gentrification

Over the last several decades, urban planners and municipalities have sought to identify and better manage the socioeconomic ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Devdiscourse

Data-driven AI approach narrows diagnostic gap between dengue and chikungunya

Dengue and chikungunya, the two mosquito-borne diseases that frequently circulate at the same time, share the same Aedes ...
IEEE

Machine Learning Techniques to Improve the Cognitive Workload Classification Using Multimodal Sensors’ Data

Abstract: Using machine learning applied to multimodal physiological data allows the classification of cognitive workload (low, moderate, or high load) during task performance. However, current ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
IEEE

Gender Classification in Panoramic Dental X-Rays using few-shot learning and Ensemble models

Abstract: Integrating advanced technologies has revolutionized dental practice, transforming patient diagnosis and treatment. Radiographic examinations remain one of the most essential tools for ...
Frontiers

Development of an interpretable machine learning model for predicting venous thromboembolism in intensive care unit patients with intracerebral hemorrhage

1 Department of Graduate School, Qinghai University, Xining, China 2 Department of Neurosurgery, Qinghai Provincial People’s Hospital, Xining, China Background: Venous thromboembolism (VTE) is a ...
Frontiers

Development of a machine learning-based risk prediction model for early-stage pneumoconiosis: a retrospective study

Background: The diagnosis of occupational pneumoconiosis requires more accurate predictive models. The purpose of this study is to screen blood markers associated with early pneumoconiosis development ...