The youth mental health crisis is exacerbated by limited access to care and resources. Mobile health (mHealth) platforms using predictive artificial intelligence (AI) can improve access and reduce barriers, enabling real-time responses and precision ...
Detecting glucose levels is crucial for diabetes patients as it enables timely and effective management, preventing complications and promoting overall health. In this endeavor, we have designed a novel, affordable point-of-care diagnostic device uti...
Journal of the American Pharmacists Association : JAPhA
Nov 6, 2024
BACKGROUND: The Food and Drug Administration mandates patient labeling materials like the Medication Guide (MG) and Instructions for Use (IFU) to support appropriate medication use. However, challenges such as low health literacy and difficulties nav...
This study evaluates the effectiveness of an Artificial Intelligence (AI)-based smartphone application designed for decay detection on intraoral photographs, comparing its performance to that of junior dentists. Conducted at The Aga Khan University H...
The image-based detection and classification of plant diseases has become increasingly important to the development of precision agriculture. We consider the case of tomato, a high-value crop supporting the livelihoods of many farmers around the worl...
IEEE transactions on bio-medical engineering
Oct 25, 2024
OBJECTIVE: To remove signal contamination in electroencephalogram (EEG) traces coming from ocular, motion, and muscular artifacts which degrade signal quality. To do this in real-time, with low computational overhead, on a mobile platform in a channe...
Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant , , and . Despite the need for rapid AMR diagnostics globally, current molecu...
Driving anger is a serious global issue that poses risks to road safety, thus necessitating the development of effective detection and intervention methods. This study investigated the feasibility of using smartphones to capture facial expressions to...
This study focuses on the integration of a custom-built and optimally trained YOLO v5 model into a smartphone app developed with Java language. A dual-modal immunochromatographic rapid detection system based on a deep learning strategy for smartphone...
Excessive Smartphone Use (ESU) poses a significant challenge in contemporary society, yet its recognition as a distinct disorder remains ambiguous. This study aims to address this gap by leveraging functional magnetic resonance imaging (fMRI) data an...
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