AI Medical Compendium Journal:
Computer methods and programs in biomedicine

Showing 51 to 60 of 844 articles

Deep-learning-based diagnosis framework for ankle-brachial index defined peripheral arterial disease of lower extremity wound: Comparison with physicians.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Few studies have evaluated peripheral artery disease (PAD) in patients with lower extremity wounds by a convolutional neural network (CNN)-based deep learning algorithm. We aimed to establish a framework for PAD detection, p...

Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries.

Computer methods and programs in biomedicine
PURPOSE: In medical deep learning, models not trained from scratch are typically fine-tuned based on ImageNet-pretrained models. We posit that pretraining on data from the domain of the downstream task should almost always be preferable.

M2OCNN: Many-to-One Collaboration Neural Networks for simultaneously multi-modal medical image synthesis and fusion.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Acquiring comprehensive information from multi-modal medical images remains a challenge in clinical diagnostics and treatment, due to complex inter-modal dependencies and missing modalities. While cross-modal medical image s...

Non-experimental rapid identification of lower respiratory tract infections in patients with chronic obstructive pulmonary disease using multi-label learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Microbiological culture is a standard diagnostic test that takes a long time to identify lower respiratory tract infections (LRTI) in patients with chronic obstructive pulmonary disease (COPD). This study entailed the develo...

SeLa-MIL: Developing an instance-level classifier via weakly-supervised self-training for whole slide image classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Pathology image classification is crucial in clinical cancer diagnosis and computer-aided diagnosis. Whole Slide Image (WSI) classification is often framed as a multiple instance learning (MIL) problem due to the high cost o...

Semi-supervised Strong-Teacher Consistency Learning for few-shot cardiac MRI image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cardiovascular disease is a leading cause of mortality worldwide. Automated analysis of heart structures in MRI is crucial for effective diagnostics. While supervised learning has advanced the field of medical image segmenta...

Convolutional neural network-based method for the real-time detection of reflex syncope during head-up tilt test.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Reflex syncope (RS) is the most common type of syncope caused by dysregulation of the autonomic nervous system. Diagnosing RS typically involves the head-up tilt test (HUTT), which tracks physiological signals such as blood...

PMFSNet: Polarized multi-scale feature self-attention network for lightweight medical image segmentation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Current state-of-the-art medical image segmentation methods prioritize precision but often at the expense of increased computational demands and larger model sizes. Applying these large-scale models to the relatively limite...

Towards practical and privacy-preserving CNN inference service for cloud-based medical imaging analysis: A homomorphic encryption-based approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cloud-based Deep Learning as a Service (DLaaS) has transformed biomedicine by enabling healthcare systems to harness the power of deep learning for biomedical data analysis. However, privacy concerns emerge when sensitive us...

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...