AIMC Topic: Early Diagnosis
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Preclinical Cognitive Markers of Alzheimer Disease and Early Diagnosis Using Virtual Reality and Artificial Intelligence: Literature Review.
JMIR medical informatics
Jan 28, 2025
BACKGROUND: This review explores the potential of virtual reality (VR) and artificial intelligence (AI) to identify preclinical cognitive markers of Alzheimer disease (AD). By synthesizing recent studies, it aims to advance early diagnostic methods t...
AI-Driven Innovations for Early Sepsis Detection by Combining Predictive Accuracy With Blood Count Analysis in an Emergency Setting: Retrospective Study.
Journal of medical Internet research
Jan 24, 2025
BACKGROUND: Sepsis, a critical global health challenge, accounted for approximately 20% of worldwide deaths in 2017. Although the Sequential Organ Failure Assessment (SOFA) score standardizes the diagnosis of organ dysfunction, early sepsis detection...
Guardian-BERT: Early detection of self-injury and suicidal signs with language technologies in electronic health reports.
Computers in biology and medicine
Jan 21, 2025
Mental health disorders, including non-suicidal self-injury (NSSI) and suicidal behavior, represent a growing global concern. Early detection of these conditions is crucial for timely intervention and prevention of adverse outcomes. In this study, we...
Efficient recognition of Parkinson's disease mice on stepping characters with CNN.
Scientific reports
Jan 20, 2025
Parkinson's disease (PD), as the second most prevalent neurodegenerative disorder worldwide, impacts the quality of life for over 12 million patients. This study aims to enhance the accuracy of early diagnosis of PD through non-invasive methods, with...
PIDGN: An explainable multimodal deep learning framework for early prediction of Parkinson's disease.
Journal of neuroscience methods
Jan 18, 2025
BACKGROUND: Parkinson's disease (PD), the second most common neurodegenerative disease in the world, is usually not diagnosed until the later stages of the disease, when patients might have already missed the best treatment period. Therefore, more ef...
Early Prediction of Cardio Vascular Disease (CVD) from Diabetic Retinopathy using improvised deep Belief Network (I-DBN) with Optimum feature selection technique.
BMC cardiovascular disorders
Jan 18, 2025
Cardio Vascular Disease (CVD) is one of the leading causes of mortality and it is estimated that 1 in 4 deaths happens due to it. The disease prevalence rate becomes higher since there is an inadequate system/model for predicting CVD at an earliest. ...
Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.
Journal of speech, language, and hearing research : JSLHR
Jan 9, 2025
PURPOSE: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review...
Exploring artificial intelligence for differentiating early syphilis from other skin lesions: a pilot study.
BMC infectious diseases
Jan 8, 2025
BACKGROUND: Early diagnosis of syphilis is vital for its effective control. This study aimed to develop an Artificial Intelligence (AI) diagnostic model based on radiomics technology to distinguish early syphilis from other clinical skin lesions.
Early detection of autism spectrum disorder: gait deviations and machine learning.
Scientific reports
Jan 6, 2025
Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder diagnosed by clinicians and experts through questionnaires, observations, and interviews. Current diagnostic practices focus on social and communication impairments, which often emerge l...
ReIU: an efficient preliminary framework for Alzheimer patients based on multi-model data.
Frontiers in public health
Jan 3, 2025
The rising incidence of Alzheimer's disease (AD) poses significant challenges to traditional diagnostic methods, which primarily rely on neuropsychological assessments and brain MRIs. The advent of deep learning in medical diagnosis opens new possibi...
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