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Apriori algorithm based prediction of students' mental health risks in the context of artificial intelligence.
Frontiers in public health
Feb 12, 2025
INTRODUCTION: The increasing prevalence of mental health challenges among college students necessitates innovative approaches to early identification and intervention. This study investigates the application of artificial intelligence (AI) techniques...
Future pharmacy practitioners' insights towards integration of artificial intelligence in healthcare education: Preliminary findings from Karachi, Pakistan.
PloS one
Feb 12, 2025
UNLABELLED: In an evolutionary era of medical education, "Artificial intelligence" (AI) is applied to replicate human intellect, encompassing abilities, logical reasoning and effective problem-solving skills. Previous research has explored the attitu...
Hybrid attention-CNN model for classification of gait abnormalities using EMG scalogram images.
Journal of medical engineering & technology
Feb 12, 2025
This research aimed to develop an algorithm for classifying scalogram images generated from electromyography data of patients with Rheumatoid Arthritis and Prolapsed Intervertebral Disc. Electromyography is valuable for assessing muscle function and ...
Eliminating the second CT scan of dual-tracer total-body PET/CT via deep learning-based image synthesis and registration.
European journal of nuclear medicine and molecular imaging
Feb 11, 2025
PURPOSE: This study aims to develop and validate a deep learning framework designed to eliminate the second CT scan of dual-tracer total-body PET/CT imaging.
Molecular structure of NRG-1 protein and its impact on adult hypertension and heart failure: A new clinical Indicator diagnosis based on advanced machine learning.
International journal of biological macromolecules
Feb 11, 2025
The purpose of this study was to investigate the molecular structure of NRG-1 protein and its mechanism of action in adult hypertensive heart failure. The amino acid sequence of NRG-1 protein was analyzed by bioinformatics method. High-throughput seq...
Machine learning for the early prediction of long-term cognitive outcome in autoimmune encephalitis.
Journal of psychosomatic research
Feb 11, 2025
BACKGROUND AND OBJECTIVE: Autoimmune encephalitis (AE) is an immune-mediated disease. Some patients experience persistent cognitive deficits despite receiving immunotherapy. We aimed to develop a prediction model for long-term cognitive outcomes in p...
Evaluation of factors predicting transition from prediabetes to diabetes among patients residing in underserved communities in the United States - A machine learning approach.
Computers in biology and medicine
Feb 11, 2025
INTRODUCTION: Over one-third of the population in the United States (US) has prediabetes. Unfortunately, underserved population in the United States face a higher burden of prediabetes compared to urban areas, increasing the risk of stroke and heart ...
Familiarity with artificial intelligence drives optimism and adoption among veterinary professionals: 2024 survey.
American journal of veterinary research
Feb 11, 2025
OBJECTIVE: To capture veterinary professionals' perspectives and applications of AI in veterinary care. This study assesses the perceived benefits, challenges, and potential areas where AI could enhance veterinary medicine and practice workflows.
A deep learning-enabled smart garment for accurate and versatile monitoring of sleep conditions in daily life.
Proceedings of the National Academy of Sciences of the United States of America
Feb 11, 2025
In wearable smart systems, continuous monitoring and accurate classification of different sleep-related conditions are critical for enhancing sleep quality and preventing sleep-related chronic conditions. However, the requirements for device-skin cou...
A novel method for screening malignant hematological diseases by constructing an optimal machine learning model based on blood cell parameters.
BMC medical informatics and decision making
Feb 11, 2025
BACKGROUND: Screening of malignant hematological diseases is of great importance for their diagnosis and subsequent treatment. This study constructed an optimal screening model for malignant hematological diseases based on routine blood cell paramete...
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