Artificial Intelligence Medical Compendium

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

Showing 42,531 to 42,540 of 223,853 articles

Spiking neural networks for video analysis: An in-depth review of models and architectures.

Neural networks : the official journal of the International Neural Network Society Mar 12, 2026
Deep Learning (DL) has revolutionized various industries, continuously evolving with new architectures and concepts. Among these, Spiking Neural Networks (SNNs) have emerged as a promising, energy-efficient, and biologically inspired computing paradi... read more 

PDAFormer 3+: A full-scale connected modified transformer with parallel dual attention for 3D medical image segmentation.

Artificial intelligence in medicine Mar 12, 2026
Medical image segmentation is essential for enhancing diagnostic and therapeutic accuracy, improving healthcare efficiency, and advancing medical research. In recent years, transformers have gained increasing attention in medical image segmentation o... read more 

DBML-Font :Double-branch multi-level feature fusion based on diffusion model for few-shot font generation.

Neural networks : the official journal of the International Neural Network Society Mar 12, 2026
Few-shot font generation refers to the task of synthesizing font images with accurate content and consistent style based on a limited set of reference samples. Although existing font generation methods demonstrate competitive performance in modeling ... read more 

SEEK: A simple defense to model hijacking attack.

Neural networks : the official journal of the International Neural Network Society Mar 12, 2026
Model hijacking attacks represent an emerging training-time threat to natural language processing systems. They compromise the model's training process, enabling the hijacked model to covertly execute attacker-specified tasks while maintaining compar... read more 

Training sparse convolutional deep predictive coding networks with attention.

Neural networks : the official journal of the International Neural Network Society Mar 12, 2026
This paper proposes a novel training methodology for sparse convolutional deep predictive coding networks with attention (DPCN-SCA). In the same spirit of self supervised learning, the method fully exploits the bidirectional architecture, and takes a... read more 

Development and temporal validation of an interpretable point score for in-hospital mortality in CLL/SLL using the U.S. National Inpatient Sample, 2016-2022.

Leukemia research Mar 12, 2026
In-hospital mortality among patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) is ∼6%, yet no validated, transparent bedside tool exists to guide acute care. We sought to develop and benchmark interpretable mortality pred... read more 

A complete blood count-based machine learning model for rapid differentiation of aplastic anemia, immune thrombocytopenia, and myelodysplastic syndromes in routine clinical practice.

Practical laboratory medicine Mar 12, 2026
BACKGROUND: Accurate differentiation of common hematologic disorders remains challenging in routine clinical practice and often requires invasive diagnostic procedures. Although complete blood count (CBC) testing is widely available, its diagnostic v... read more 

Hierarchical attention-assisted feature pyramid network with Variational Sparse Autoencoder for cancer classification using gene data.

Computational biology and chemistry Mar 12, 2026
Analyzing gene expression data is essential for predicting and detecting diseases, including cancer. The data is very repetitive and noisy, which makes it hard to find important information about illnesses. In the past decade, several traditional mac... read more 

Towards the future of Endocrine Laboratory Medicine: defining the role of laboratory medicine specialists to strengthen the clinical-biological partnership - a joint opinion paper of EFLM-C:YS, IFCC TF-YS, and ESE-EYES.

Clinical chemistry and laboratory medicine Mar 12, 2026
Clinical endocrinology relies critically on high-quality biochemical data for diagnosis, therapeutic decisions, and long-term patient monitoring. As endocrine diagnostics grow more complex due to expanding test menus, technological advances, and chan... read more 

Automated deep-learning quantification of nine patellofemoral instability parameters on multislice CT images : development and validation of the GU2Net model.

Bone & joint open Mar 12, 2026
AIMS: Objective and precise measurement of patellar instability (PI) parameters on CT images is essential for accurate diagnosis and treatment planning. However, manual assessment is tedious, time-consuming, and prone to error. This study aimed to de... read more 
Popular Topics
Recent Journals