AIMC Topic: Early Diagnosis

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Optimizing the early diagnosis of neurological disorders through the application of machine learning for predictive analytics in medical imaging.

Scientific reports
Early diagnosis of Neurological Disorders (ND) such as Alzheimer's disease (AD) and Brain Tumors (BT) can be highly challenging since these diseases cause minor changes in the brain's anatomy. Magnetic Resonance Imaging (MRI) is a vital tool for diag...

Attention-driven hybrid deep learning and SVM model for early Alzheimer's diagnosis using neuroimaging fusion.

BMC medical informatics and decision making
Alzheimer's Disease (AD) poses a significant global health challenge, necessitating early and accurate diagnosis to enable timely interventions. AD is a progressive neurodegenerative disorder that affects millions worldwide and is one of the leading ...

A comprehensive study based on machine learning models for early identification Mycoplasma pneumoniae infection in segmental/lobar pneumonia.

Scientific reports
Segmental/lobar pneumonia in children following Mycoplasma pneumoniae (MP) infection has a significant threat to the children's health, so early recognition of MP infection is critical to reduce the severity and improve the prognosis of segmental/lob...

Design of a deep fusion model for early Parkinson's disease prediction using handwritten image analysis.

Scientific reports
Parkinson's Disease (PD) is a deteriorating condition that mostly affects older people. The lack of conclusive treatment for PD makes diagnosis very challenging. However, using patterns like tremors for early diagnosis, handwriting analysis has becom...

Early detection of Alzheimer's disease using small RNAs. Results from the EPAD cohort.

The journal of prevention of Alzheimer's disease
BACKGROUND: Alzheimer's disease (AD) is the most common form of dementia, and early diagnosis is crucial to enable effective interventions. Currently, Alzheimer's disease is diagnosed through cognitive assessments, brain imaging and fluid biomarkers ...

Predictive modeling for early detection of refractory esophageal stricture following esophageal atresia surgery: insight from a machine learning study.

Pediatric surgery international
BACKGROUND: Refractory esophageal stricture (RES) presents a challenging complication after esophageal atresia (EA) repair. Earlier identification of patients with RES could help clinical decision-making. However, there are currently limited articles...

Comparative investigation of bagging enhanced machine learning for early detection of HCV infections using class imbalance technique with feature selection.

PloS one
Around 1.5 million new cases of Hepatitis C Virus (HCV) are diagnosed globally each year (World Health Organization, 2023). Consequently, there is a pressing need for early diagnostic methods for HCV. This study investigates the prognostic accuracy o...

The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.

The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. ...

Enhancing early detection and treatment of psychosis in Germany: a protocol for the health economic evaluation of an artificial intelligence-guided complex intervention.

BMJ open
INTRODUCTION: Psychosis, characterised by chronic symptoms often emerging in youth, imposes a substantial burden on individuals and healthcare systems. While early detection and intervention can mitigate this burden, there is limited evidence on the ...

A machine-learning-based approach to predict early hallmarks of progressive hearing loss.

Hearing research
Machine learning (ML) techniques are increasingly being used to improve disease diagnosis and treatment. However, the application of these computational approaches to the early diagnosis of age-related hearing loss (ARHL), the most common sensory def...