AI Medical Compendium

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

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Adaptive cascade decoders for segmenting challenging regions in medical images.

Computers in biology and medicine
CNN-based techniques have achieved impressive outcomes in medical image segmentation but struggle to capture long-term dependencies between pixels. The Transformer, with its strong feature extraction and representation learning abilities, performs ex...

PTSP-BERT: Predict the thermal stability of proteins using sequence-based bidirectional representations from transformer-embedded features.

Computers in biology and medicine
Thermophilic proteins, mesophiles proteins and psychrophilic proteins have wide industrial applications, as enzymes with different optimal temperatures are often needed for different purposes. Convenient methods are needed to determine the optimal te...

TSegLab: Multi-stage 3D dental scan segmentation and labeling.

Computers in biology and medicine
This study introduces a novel deep learning approach for 3D teeth scan segmentation and labeling, designed to enhance accuracy in computer-aided design (CAD) systems. Our method is organized into three key stages: coarse localization, fine teeth segm...

DCSENets: Interpretable deep learning for patient-independent seizure classification using enhanced EEG-based spectrogram visualization.

Computers in biology and medicine
Neurologists often face challenges in identifying epileptic activities within multichannel EEG recordings, requiring extensive hours of analysis. Computer-aided diagnosis systems have been proposed to reduce manual inspection of EEG signals by neurol...

3D MFA: An automated 3D Multi-Feature Attention based approach for spine segmentation using a multi-stage network pruning.

Computers in biology and medicine
Spine segmentation poses significant challenges due to the complex anatomical structure of the spine and the variability in imaging modalities, which often results in unclear boundaries and overlaps with surrounding tissues. In this research, a novel...

Pinning down the accuracy of physics-informed neural networks under laminar and turbulent-like aortic blood flow conditions.

Computers in biology and medicine
BACKGROUND: Physics-informed neural networks (PINNs) are increasingly being used to model cardiovascular blood flow. The accuracy of PINNs is dependent on flow complexity and could deteriorate in the presence of highly-dynamical blood flow conditions...

Optimizing convolutional neural networks for Chronic Obstructive Pulmonary Disease detection in clinical computed tomography imaging.

Computers in biology and medicine
We aim to optimize the binary detection of Chronic Obstructive Pulmonary Disease (COPD) based on emphysema presence in the lung with convolutional neural networks (CNN) by exploring manually adjusted versus automated window-setting optimization (WSO)...

A novel case-based reasoning system for explainable lung cancer diagnosis.

Computers in biology and medicine
Lung cancer is a leading cause of cancer death worldwide. The survival rate is generally higher when this disease is detected in its early stages. Advances in artificial intelligence (AI) have enabled the development of decision support systems that ...

Automated detection of posterior urethral valves in voiding cystourethrography images: A novel AI-Based pipeline for enhanced diagnosis and classification.

Computers in biology and medicine
INTRODUCTION: Posterior Urethral Valves (PUV) are rare congenital anomalies of the male urinary tract that can lead to urethral obstruction and increased risk of kidney disease. Traditional diagnosis relies on subjective interpretation of imaging tec...

Local interpretable model-agnostic explanation approach for medical imaging analysis: A systematic literature review.

Computers in biology and medicine
BACKGROUND: The interpretability and explainability of machine learning (ML) and artificial intelligence systems are critical for generating trust in their outcomes in fields such as medicine and healthcare. Errors generated by these systems, such as...