AIMC Topic: Early Diagnosis
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Deep Ensemble learning and quantum machine learning approach for Alzheimer's disease detection.
Scientific reports
Jun 20, 2024
Alzheimer disease (AD) is among the most chronic neurodegenerative diseases that threaten global public health. The prevalence of Alzheimer disease and consequently the increased risk of spread all over the world pose a vital threat to human safekeep...
Non-Invasive Detection of Early-Stage Fatty Liver Disease via an On-Skin Impedance Sensor and Attention-Based Deep Learning.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Jun 17, 2024
Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going undiagnosed, potentially progressing to liver cirrhosis and cancer. A non-invasive and cost-effective detection method for early-stage NAFLD detection i...
Systematic Review and Meta-Analysis of Prehospital Machine Learning Scores as Screening Tools for Early Detection of Large Vessel Occlusion in Patients With Suspected Stroke.
Journal of the American Heart Association
Jun 14, 2024
BACKGROUND: Enhanced detection of large vessel occlusion (LVO) through machine learning (ML) for acute ischemic stroke appears promising. This systematic review explored the capabilities of ML models compared with prehospital stroke scales for LVO pr...
sMRI-ADNet: an interpretable deep learning framework integrating Euclidean-graph representations of Alzheimer's disease solely from structural MRI.
Magma (New York, N.Y.)
Jun 13, 2024
OBJECTIVE: To establish a multi-dimensional representation solely on structural MRI (sMRI) for early diagnosis of AD.
Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.
Annals of medicine
May 30, 2024
BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity.
Predicting autism traits from baby wellness records: A machine learning approach.
Autism : the international journal of research and practice
May 29, 2024
Timely identification of autism spectrum conditions is a necessity to enable children to receive the most benefit from early interventions. Emerging technological advancements provide avenues for detecting subtle, early indicators of autism from rout...
Comparative analysis of machine learning versus traditional method for early detection of parental depression symptoms in the NICU.
Frontiers in public health
May 28, 2024
INTRODUCTION: Neonatal intensive care unit (NICU) admission is a stressful experience for parents. NICU parents are twice at risk of depression symptoms compared to the general birthing population. Parental mental health problems have harmful long-te...
A machine learning analysis of predictors of future hypertension in a young population.
Minerva cardiology and angiology
May 27, 2024
BACKGROUND: Early diagnosis of hypertension (HT) is crucial for preventing end-organ damage. This study aims to identify the risk factors for future HT in young individuals through the application of machine learning (ML) models.
Early diagnosis of persons with von Willebrand disease using a machine learning algorithm and real-world data.
Expert review of hematology
May 24, 2024
BACKGROUND: Von Willebrand disease (VWD) is underdiagnosed, often delaying treatment. VWD claims coding is limited and includes no severity qualifiers; improved identification methods for VWD are needed. The aim of this study is to identify and chara...
Medical forecasting.
Science (New York, N.Y.)
May 23, 2024
"AI-Powered Forecasting" was recently on the cover of , highlighting a new deep learning model for much faster and more accurate weather forecasting. Known as GraphCast, it outperformed the gold-standard system and had an accuracy of 99.7% for tropos...
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