AIMC Topic: Early Diagnosis

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TdCCA with Dual-Modal Signal Fusion: Degenerated Occipital and Frontal Connectivity of Adult Moyamoya Disease for Early Identification.

Translational stroke research
Cognitive impairment in patients with moyamoya disease (MMD) manifests earlier than clinical symptoms. Early identification of brain connectivity changes is essential for uncovering the pathogenesis of cognitive impairment in MMD. We proposed a tempo...

Machine Learning Models as Early Warning Systems for Neonatal Infection.

Clinics in perinatology
Neonatal infections pose a significant threat to the health of newborns. Associated morbidity and mortality risks underscore the urgency of prompt diagnosis and treatment with appropriate empiric antibiotics. Delay in treatment can be fatal; thus, ea...

Identification of a machine learning-based diagnostic model for axial spondyloarthritis in rheumatological routine care using a random forest approach.

RMD open
OBJECTIVES: In axial spondyloarthritis (axSpA), early diagnosis is crucial, but diagnostic delay remains long and diagnostic criteria do not exist. We aimed to identify a diagnostic model that distinguishes patients with axSpA from patients without a...

Early diagnostic value of home video-based machine learning in autism spectrum disorder: a meta-analysis.

European journal of pediatrics
UNLABELLED: Machine learning (ML) based on remote video has shown ideal diagnostic value in autism spectrum disorder (ASD). Here, we conducted a meta-analysis of the diagnostic value of home video-based ML in ASD. Relevant articles were systematicall...

Explainable Deep Learning Approaches for Risk Screening of Periodontitis.

Journal of dental research
Several pieces of evidence have been reported regarding the association between periodontitis and systemic diseases. Despite the emphasized significance of prevention and early diagnosis of periodontitis, there is still a lack of a clinical tool for ...

Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases.

Scientific reports
Machine learning has gained attention in the medical field. Continuous efforts are being made to develop robust models for early prognosis purposes. The brain is the most pivotal organ in the human body. A brain stroke is generally caused by a blocka...

Role of artificial intelligence in early diagnosis and treatment of infectious diseases.

Infectious diseases (London, England)
Infectious diseases remain a global health challenge, necessitating innovative approaches for their early diagnosis and effective treatment. Artificial Intelligence (AI) has emerged as a transformative force in healthcare, offering promising solution...

Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Validation.

JMIR formative research
BACKGROUND: The underdiagnosis of cognitive impairment hinders timely intervention of dementia. Health professionals working in the community play a critical role in the early detection of cognitive impairment, yet still face several challenges such ...

Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.

Scientific reports
Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effec...

Machine learning-based identification and validation of immune-related biomarkers for early diagnosis and targeted therapy in diabetic retinopathy.

Gene
The early diagnosis of diabetic retinopathy (DR) is challenging, highlighting the urgent need to identify new biomarkers. Immune responses play a crucial role in DR, yet there are currently no reports of machine learning (ML) algorithms being utilize...