AIMC Topic: Early Diagnosis

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Development and validation of a deep learning model for early detection and screening of diabetic retinopathy.

BMC medical informatics and decision making
Early diagnosis and screening of diabetic retinopathy (DR) are crucial for reducing medical burdens and conserving healthcare resources. This study introduces an advanced AI-assisted recognition system designed to enhance the detection of DR lesions ...

Lightweight early detection of knee osteoarthritis in athletes.

Scientific reports
Osteoarthritis (OA) is a prevalent condition among athletes, characterized by the progressive degradation of joint cartilage, particularly in weight-bearing joints such as the knees. Early detection is critical for effective management and prevention...

Enhancing the early detection of Alzheimer's disease using an integrated CNN-LSTM framework: A robust approach for fMRI-based multi-stage classification.

PloS one
Alzheimer's Disease poses a significant challenge as a progressive and irreversible neurological condition striking the elderly population. Its incurable nature correlates with a significant rise in death rates. However, early detection can slow its ...

Investigation into the Classification of Cough Sounds for Early Asthma Screening.

Current allergy and asthma reports
PURPOSE OF REVIEW: This review aims to explore an effective and scalable approach for early asthma detection using cough sounds. The main objective is to evaluate whether a multi-model deep learning fusion framework can improve diagnostic accuracy an...

Transforming sepsis management: AI-driven innovations in early detection and tailored therapies.

Critical care (London, England)
Sepsis remains a leading cause of mortality worldwide, driven by its clinical complexity and delayed recognition. Artificial intelligence (AI) offers promising solutions to improve sepsis care through earlier detection, risk stratification, and perso...

Early detection of vascular catheter-associated infections employing supervised machine learning - a case study in Lleida region.

BMC medical informatics and decision making
Healthcare-associated infections (HAIs), particularly Vascular Catheter-Associated Infections (VCAIs), are a significant concern, accounting for over 7% of all infections and are often linked to medical devices. Early detection of VCAIs before invasi...

Improving early detection of Alzheimer's disease through MRI slice selection and deep learning techniques.

Scientific reports
Alzheimer's disease is a progressive neurodegenerative disorder marked by cognitive decline, memory loss, and behavioral changes. Early diagnosis, particularly identifying Early Mild Cognitive Impairment (EMCI), is vital for managing the disease and ...

The role of artificial intelligence in early detection and intervention of coronary artery disease.

Current opinion in cardiology
PURPOSE OF REVIEW: The diagnosis and management of coronary artery disease (CAD) involves complex delivery of care. Artificial intelligence (AI) proves to be a timely solution to challenges with diagnostics and timely and appropriate, quality of care...

Comparison of machine learning models for mucopolysaccharidosis early diagnosis using UAE medical records.

Scientific reports
Rare diseases, such as Mucopolysaccharidosis (MPS), present significant challenges to the healthcare system. Some of the most critical challenges are the delay and the lack of accurate disease diagnosis. Early diagnosis of MPS is crucial, as it has t...

Ultra-early detection of S100B biomarkers using a nanophotonic biosensor with deep learning quantification: A clinical model based on EDAS patients.

Biosensors & bioelectronics
BACKGROUND: Ultra-early detection of brain injury biomarkers within the critical first hour post-injury remains a major clinical challenge in mild traumatic brain injury (mTBI) management. Conventional platforms (e.g., ELISA) suffer from limited sens...