AI Medical Compendium Topic

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Diagnosis, Computer-Assisted

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A deep architecture based on attention mechanisms for effective end-to-end detection of early and mature malaria parasites in a realistic scenario.

Computers in biology and medicine
BACKGROUND: Malaria is a critical and potentially fatal disease caused by the Plasmodium parasite and is responsible for more than 600,000 deaths globally. Early and accurate detection of malaria parasites is crucial for effective treatment, yet conv...

A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.

Scientific reports
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretatio...

Two algorithms for improving model-based diagnosis using multiple observations and deep learning.

Neural networks : the official journal of the International Neural Network Society
Model-based diagnosis (MBD) is a critical problem in artificial intelligence. Recent advancements have made it possible to address this challenge using methods like deep learning. However, current approaches that use deep learning for MBD often strug...

Severity grading of hypertensive retinopathy using hybrid deep learning architecture.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Hypertensive Retinopathy (HR) is a retinal manifestation resulting from persistently elevated blood pressure. Severity grading of HR is essential for patient risk stratification, effective management, progression monitoring...

Multiscale feature enhanced gating network for atrial fibrillation detection.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Atrial fibrillation (AF) is a significant cause of life-threatening heart disease due to its potential to lead to stroke and heart failure. Although deep learning-assisted diagnosis of AF based on ECG holds significance in c...

Residual-attention deep learning model for atrial fibrillation detection from Holter recordings.

Journal of electrocardiology
BACKGROUND: Detecting subtle patterns of atrial fibrillation (AF) and irregularities in Holter recordings is intricate and unscalable if done manually. Artificial intelligence-based techniques can be beneficial. In fact, with the rapid advancement of...

Breast cancer classification based on hybrid CNN with LSTM model.

Scientific reports
Breast cancer (BC) is a global problem, largely due to a shortage of knowledge and early detection. The speed-up process of detection and classification is crucial for effective cancer treatment. Medical image analysis methods and computer-aided diag...

A deep ensemble learning framework for glioma segmentation and grading prediction.

Scientific reports
The segmentation and risk grade prediction of gliomas based on preoperative multimodal magnetic resonance imaging (MRI) are crucial tasks in computer-aided diagnosis. Due to the significant heterogeneity between and within tumors, existing methods ma...

Computer-aided cholelithiasis diagnosis using explainable convolutional neural network.

Scientific reports
Accurate and precise identification of cholelithiasis is essential for saving the lives of millions of people worldwide. Although several computer-aided cholelithiasis diagnosis approaches have been introduced in the literature, their use is limited ...

Advances in colorectal cancer diagnosis using optimal deep feature fusion approach on biomedical images.

Scientific reports
Colorectal cancer (CRC) is the second popular cancer in females and third in males, with an increased number of cases. Pathology diagnoses complemented with predictive and prognostic biomarker information is the first step for personalized treatment....