AIMC Topic: Early Diagnosis

Clear Filters Showing 21 to 30 of 522 articles

A novel approach hybrid of ensemble learning and 3-D CNN mechanism: early-stage diagnosis of Alzheimer's disease using EEG signals.

Scientific reports
Alzheimer's disease (AD) is a progressive neurological disorder that causes brain cell degeneration and leads to dementia. Early and accurate detection of AD is crucial, as it allows timely treatment before the brain suffers permanent damage. In rece...

Multi-modal deep-attention-BiLSTM based early detection of mental health issues using social media posts.

Scientific reports
The rising prevalence of mental health disorders such as depression, anxiety, and bipolar disorder underscores the urgent need for effective tools to enable early detection and intervention. Social media platforms like Reddit offer a rich source of u...

Multi-modal deep learning framework for early detection of Parkinson's disease using neurological and physiological data for high-fidelity diagnosis.

Scientific reports
Parkinson's disease (PD) is a progressive neurodegenerative disorder that remained challenging for proper diagnosis in its early stages due to its heterogeneous symptom presentation and overlapping clinical features. Consequently, there is no consens...

An ensemble model based on transfer learning for the early detection of Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by the gradual decline in cognitive functions, particularly memory and reasoning. Early detection, especially during cognitive impairment (MCI) stage, is crucial for t...

Early diagnosis of knee osteoarthritis severity using vision transformer.

BMC musculoskeletal disorders
Knee Osteoarthritis (K-OA) is characterized as a progressive joint condition with global prevalence, exhibiting deterioration over time and impacting a significant portion of the population. It happens because joints wear out slowly. The main reason ...

Ratio of haemorrhagic area to retinal area as a novel indicator for AI-based screening of diabetic retinopathy in type 2 diabetes: a community-based cross-sectional study.

BMJ open
BACKGROUND: The application of artificial intelligence (AI) technology in the screening of diabetic retinopathy (DR) has made significant strides. However, there remains a lack of comprehensive validation and evaluation of AI-derived quantitative ind...

FetalDenseNet: multi-scale deep learning for enhanced early detection of fetal anatomical planes in prenatal ultrasound.

Journal of perinatal medicine
OBJECTIVES: The study aims to improve the classification of fetal anatomical planes using Deep Learning (DL) methods to enhance the accuracy of fetal ultrasound interpretation.

Micro- and nanoscale biosensing technologies for early diagnosis of Parkinson's disease.

Mikrochimica acta
Parkinson's disease (PD), the second most prevalent neurodegenerative disorder, remains challenging to diagnose at its earliest stages due to the absence of definitive biomarkers and overlapping clinical features with other synucleinopathies, thereby...

A Machine Learning-Driven Cyclic Optimizing Strategy for the Construction of Paper-Based Microfluidic Devices in the Early Diagnosis of Periodontitis.

ACS sensors
The lack of effective optimization strategies hinders the optimal performance of paper-based microfluidic analytical devices (μPADs). In this work, a Machine Learning-driven Computer vision-BP Neural Networks-Genetic Algorithm-based Cyclic Optimizing...

AlzFormer: Video-based space-time attention model for early diagnosis of Alzheimer's disease.

Neuroscience
Early and accurate Alzheimer's disease (AD) diagnosis is critical for effective intervention, but it is still challenging due to neurodegeneration's slow and complex progression. Recent studies in brain imaging analysis have highlighted the crucial r...