AI Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

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A comprehensive scoping review on machine learning-based fetal echocardiography analysis.

Computers in biology and medicine
Fetal echocardiography (ultrasound of the fetal heart) plays a vital role in identifying heart defects, allowing clinicians to establish prenatal and postnatal management plans. Machine learning-based methods are emerging to support the automation of...

VcaNet: Vision Transformer with fusion channel and spatial attention module for 3D brain tumor segmentation.

Computers in biology and medicine
Accurate segmentation of brain tumors from MRI scans is a critical task in medical image analysis, yet it remains challenging due to the complex and variable nature of tumor shapes and sizes. Traditional convolutional neural networks (CNNs), while ef...

Weakly-supervised thyroid ultrasound segmentation: Leveraging multi-scale consistency, contextual features, and bounding box supervision for accurate target delineation.

Computers in biology and medicine
Weakly-supervised learning (WSL) methods have gained significant attention in medical image segmentation, but they often face challenges in accurately delineating boundaries due to overfitting to weak annotations such as bounding boxes. This issue is...

Integrating genetics, metabolites, and clinical characteristics in predicting cardiometabolic health outcomes using machine learning algorithms - A systematic review.

Computers in biology and medicine
BACKGROUND: Machine learning (ML) integration of clinical, metabolite, and genetic data reveals variable results in predicting cardiometabolic health (CMH) outcomes. Therefore, we aim to (1) evaluate whether a multi-modal approach incorporating all t...

Glo-net: A dual task branch based neural network for multi-class glomeruli segmentation.

Computers in biology and medicine
Accurate segmentation and classification of glomeruli are fundamental to histopathology slide analysis in renal pathology, which helps to characterize individual kidney disease. Accurate segmentation of glomeruli of different types faces two main cha...

Colorectal cancer classification using weakly annotated whole slide images: Multiple instance learning optimization study.

Computers in biology and medicine
Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is rapidly increasing due to many factors, such as unhealthy lifestyles, water and food pollution, aging, and medical diagnosis development. Detecting CRC in its e...

Integrating CNN and Bi-LSTM for protein succinylation sites prediction based on Natural Language Processing technique.

Computers in biology and medicine
Protein succinylation, a post-translational modification wherein a succinyl group (-CO-CH₂-CH₂-CO-) attaches to lysine residues, plays a critical regulatory role in cellular processes. Dysregulated succinylation has been implicated in the onset and p...

TinyML and edge intelligence applications in cardiovascular disease: A survey.

Computers in biology and medicine
Tiny machine learning (TinyML) and edge intelligence have emerged as pivotal paradigms for enabling machine learning on resource-constrained devices situated at the extreme edge of networks. In this paper, we explore the transformative potential of T...

FocusUNet: Pioneering dual attention with gated U-Net for colonoscopic polyp segmentation.

Computers in biology and medicine
The detection and excision of colorectal polyps, precursors to colorectal cancer (CRC), can improve survival rates by up to 90%. Automated polyp segmentation in colonoscopy images expedites diagnosis and aids in the precise identification of adenomat...

Patch-based feature mapping with generative adversarial networks for auxiliary hip fracture detection.

Computers in biology and medicine
BACKGROUND: Hip fractures are a significant public health issue, particularly among the elderly population. Pelvic radiographs (PXRs) play a crucial role in diagnosing hip fractures and are commonly used for their evaluation. Previous research has de...