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

Predictive Modeling for Water Anomaly Detection Using Machine Learning

Abstract: Water scarcity along with poor management of water sources is turning to be a matter of global concern, and this calls for an intelligent monitoring system. This paper introduces a new ...
IEEE

Ground Water Quality Analysis with Real-Time Data Using Machine Learning

Abstract: For the entire world Ground water is considered as the predominant source of water used for various purposes. As far as India is concerned 65% of its needs are satisfied by ground water. But ...
IEEE

Smart Healthcare: Early Diagnosis of Fetal Health Conditions using Machine Learning and Cardiotocographic Data

Abstract: Fetal health and early diagnosis refer to fetal development and regular contact with the mother’s uterus during pregnancy. Maximum pregnancy period complications put the fetus in a ...
IEEE

FloodNet-Lite: A Lightweight Deep Learning for Flood Mapping Using Remote Sensing Data With Optimized UNet and Edge Deployment Approach in 6G

Abstract: Flood mapping using remote sensing data is critical to disaster response, especially in real-time monitoring and edge deployment. However, existing deep-learning (DL) models often face ...
Frontiers

Machine learning approaches to predict hip fracture incidence: insights from the CHARLS dataset

Background: Hip fractures are a major health concern in the older adults, severely impacting patients’ quality of life and straining healthcare systems. With China’s aging population, their incidence ...
IEEE

Shape-Based Force Prediction of a Soft SMA Planar Actuator Using Machine Learning

Abstract: Soft actuators driven by shape memory alloy (SMA) wires are capable of undergoing a large deformation and offering a fast response, which allows them to assemble soft robots for diverse ...
IEEE

Data-Driven Solutions for Human Trafficking: Detection and Impact Analysis Using Machine Learning

Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...
Frontiers

Data-driven AI approaches for screening high-efficiency, stable, and lead-free perovskite photovoltaic materials: a review

1 Xi’an Key Laboratory of Advanced Photo-Electronics Materials and Energy Conversion Device, School of Electronic Information, Xijing University, Xi’an, China 2 Beijing Chaoyang Foreign Language ...
IEEE

Estimating Spatio-Temporally Continuous GEDI Aboveground Biomass Density During 2015-2020 From Multi-Source Data Using Machine Learning and Deep Learning

Abstract: Accurate estimation of forest aboveground biomass density is essential for quantifying terrestrial carbon exchange. NASA's Global Ecosystem Dynamics Investigation (GEDI) LiDAR mission has ...
IEEE

Predictive Modeling for Tourist Arrivals: Assessing the Impact of Weather Data Using Machine Learning Models

Abstract: This pioneering study explores the impact of incorporating weather data into the prediction of tourism demand in Sri Lanka, marking one of the first assessments of its kind in this context.