AIMC Topic: Diagnosis, Computer-Assisted

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A systematic literature review on mammography: deep learning techniques for breast cancer detection with global and Asian perspectives.

BMC cancer
PURPOSE: Breast cancer remains a leading cause of mortality in women worldwide, with notable disparities in incidence and prognosis across regions. This systematic review explores the application of Deep Learning-based computer-aided diagnostic (CAD)...

ECG beat classification with fractional order differentiator and machine learning techniques.

Biomedical physics & engineering express
Electrocardiogram (ECG) is essential for assessing heart function, but manual analysis is time-consuming and error-prone. Automated ECG analysis can improve early detection of cardiovascular diseases by accurately identifying abnormal beats despite s...

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...

A Multimodal Convolutional Neural Network Model for Parkinson's Disease Diagnosis Based on Fused Handwriting Dynamics Signals.

Journal of medical systems
Parkinson's disease (PD) is a prevalent and complex neurodegenerative disorder, with early diagnosis playing a critical role in timely treatment and management. Handwriting dynamics has emerged as a promising biomarker for early detection of PD, yet ...

Transfer learning with fuzzy decision support for multi-class lung disease classification: performance analysis of pre-trained CNN models.

Scientific reports
Accurate and efficient classification of lung diseases from medical images remains a significant challenge in computer-aided diagnosis systems. This research presents a novel approach integrating transfer learning techniques with fuzzy decision suppo...

AI-driven prognostics in pediatric bone marrow transplantation: a CAD approach with Bayesian and PSO optimization.

BMC medical informatics and decision making
Bone marrow transplantation (BMT) is a critical treatment for various hematological diseases in children, offering a potential cure and significantly improving patient outcomes. However, the complexity of matching donors and recipients and predicting...

Deep learning-aided optical biopsy achieves whole-chain diagnosis of Correa cascade of gastric cancer: a prospective study.

BMC medicine
BACKGROUND: Biopsies are essential in differentiating benign from malignant lesions in routine gastroscopy. Nevertheless, redundant biopsies increase patients' expenses and pathologists' workload. Probe-based confocal laser endomicroscopy (pCLE) enab...

Development of deep learning-based narrow-band imaging endocytoscopic classification for predicting colorectal lesions from a retrospective study.

Nature communications
Data-driven approaches have advanced colorectal lesion diagnosis in digestive endoscopy, yet their application in endocytoscopy (EC)-a high-magnification imaging technique-remains limited, with most studies relying on conventional machine learning me...

Machine learning-based CAD detection using integrated ECG and PCG parameter features.

Biomedical physics & engineering express
The combined analysis of electrocardiogram (ECG) and phonocardiogram signals(PCG) has demonstrated significant potential in the non-invasive detection of coronary artery disease (CAD). The efficacy of combining cardiac pathological parameters such as...