Artificial Intelligence Medical Compendium

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

Showing 60,281 to 60,290 of 228,072 articles

Marine natural products.

Natural product reports
Covering: January to the end of December 2024This review covers the literature published in 2024 for marine natural products (MNPs), with 617 citations (578 for the period January to December 2024) referring to compounds isolated from marine microorg... read more 

Development and Validation of a Urinary Exosomal miRNA Diagnostic Panel for Early Detection of Esophageal Cancer.

Cancer science
Esophageal squamous cell carcinoma (ESCC) remains a leading cause of cancer-related mortality, with early detection being challenging. Although endoscopic screening can aid in diagnosis, its invasiveness and cost limit widespread compliance. To addre... read more 

Automation of Fluorescence-Activated Droplet Release by Deep-Learning-Based Droplet Detector.

IEEE transactions on nanobioscience
Droplet-based microfluidics enables miniaturized, high-throughput biochemical assays but faces challenges in selective droplet retrieval, particularly after long-term monitoring. While light-induced bubble generation offers a promising, hardware-simp... read more 

Channel Modeling for Mobile Molecular Communication with Anomalous Diffusion by Deep Neural Network.

IEEE transactions on nanobioscience
Diffusion-based mobile molecular communication (MMC) systems have shown great potential in nanoscale communication, particularly in the scenarios involving anomalous diffusion. Accurately modeling the anomalous diffusion channel of MMC system with mu... read more 

EEGMoE: A Domain-Decoupled Mixture-of-Experts Model for Self-Supervised EEG Representation Learning.

IEEE transactions on neural networks and learning systems
Existing deep learning models for electroencephalogram (EEG) are typically tailored for specific tasks, datasets, or even subjects. This specialization restricts their applicability, reducing both perceptual capabilities and overall generalizability.... read more 

A General Image Fusion Approach Exploiting Gradient Transfer Learning and Fusion Rule Unfolding.

IEEE transactions on pattern analysis and machine intelligence
The goal of a deep learning-based general image fusion method is to solve multiple image fusion tasks with a single model, thereby facilitating the deployment of models in practical applications. However, existing methods fail to provide an efficient... read more 

Classification of Alzheimer's Disease by Modeling Brain Networks as Signed Networks under Deep Learning Frameworks.

IEEE transactions on computational biology and bioinformatics
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that remains a global challenge due to its complex pathology and the lack of definitive diagnostic tools. This paper introduces an innovative approach to predicting and analyzing Al... read more 

Prediction of Retinopathy of Prematurity and Treatment in Very Low Birth Weight Infants Using Machine Learning on Nationwide Non-Imaging Clinical Data.

Neonatology
INTRODUCTION: Retinopathy of prematurity (ROP) remains a leading cause of preventable blindness in preterm infants. This study aimed to develop machine learning (ML) models using non-imaging clinical data to predict ROP, severe ROP (sROP), and treate... read more 

Integrative Image Processing Framework for Enhanced Detection of Leprosy-Associated Chronic Wounds.

The international journal of lower extremity wounds
Automated leprosy chronic wound analysis from smartphone-acquired images remains hindered by uneven illumination, indistinct lesion margins, and poor spatial-textural integration. The CO-WinF framework introduces three specialized modules: AINCE, whi... read more 

Morphometric analysis and its application in lupus nephritis: a systematic review.

Journal of histotechnology
Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE), characterized by marked histological heterogeneity and high interobserver variability in the evaluation of renal biopsies. Digital morphometry has emerged as an obj... read more