Artificial Intelligence Medical Compendium
Explore the latest research on artificial intelligence and machine learning in medicine.
Showing 45,801 to 45,810 of 224,055 articles
DeepArousal-Net: A Multi-Block Recurrent Deep Learning Model for Proactive Forecasting of Non-Apneic Arousals From Multichannel PSG.
IEEE transactions on bio-medical engineering
Mar 1, 2026
OBJECTIVE: This study aimed to develop a deep learning model capable of accurately forecasting non-apneic sleep arousals, which are brief awakenings that disrupt sleep continuity and contribute to daytime fatigue. METHODS: We introduce DeepArousal-Ne... read more
Meta-Learning With Unlabeled Query Updating and Consistency Learning for Few-Shot OCT Image Classification.
IEEE transactions on bio-medical engineering
Mar 1, 2026
OBJECTIVE: Deep neural networks are widely used in the field of optical coherence tomography (OCT) to screen some common retinal diseases. However, for rare diseases with fewer cases for model training, it is challenging to achieve automatic diagnosi... read more
Back to the Future-Cardiovascular Imaging From 1966 to Today and Tomorrow.
Investigative radiology
Mar 1, 2026
This article, on the 60th anniversary of the journal Investigative Radiology , a journal dedicated to cutting-edge imaging technology, discusses key historical milestones in CT and MRI technology, as well as the ongoing advancement of contrast agent ... read more
Analysis and Control of Semi-Markov Jump Linear Systems Under Persistent Disturbances via Full Utilization of Fragmentary Kernel.
IEEE transactions on cybernetics
Mar 1, 2026
This article treats the problems of the stability, boundedness, and stabilizing control of discrete-time semi-Markov jump systems (SMJSs) with fragmentary semi-Markov kernel (SMK) under persistent disturbances. Since the statistical characteristics o... read more
Physics-Driven Neural Compensation for Electrical Impedance Tomography.
IEEE transactions on pattern analysis and machine intelligence
Mar 1, 2026
Electrical Impedance Tomography (EIT) provides a non-invasive, portable imaging modality with significant potential in medical and industrial applications. Despite its advantages, EIT encounters two primary challenges: the ill-posed nature of its inv... read more
Semantic Correspondence: Unified Benchmarking and a Strong Baseline.
IEEE transactions on pattern analysis and machine intelligence
Mar 1, 2026
Establishing semantic correspondence is a challenging task in computer vision, aiming to match keypoints with the same semantic information across different images. Benefiting from the rapid development of deep learning, remarkable progress has been ... read more
Two Decades of Multi-View Clustering: Taxonomy, Application, and Challenge.
IEEE transactions on pattern analysis and machine intelligence
Mar 1, 2026
Multi-view clustering (MVC), as an important machine learning task, aims to group data into distinct groups by leveraging complementary and consistent information across multiple views. During the last two decades, it has been widely studied, and man... read more
From System 1 to System 2: A Survey of Reasoning Large Language Models.
IEEE transactions on pattern analysis and machine intelligence
Mar 1, 2026
Achieving human-level intelligence requires refining the transition from the fast, intuitive System 1 to the slower, more deliberate System 2 reasoning. While System 1 excels in quick, heuristic decisions, System 2 relies on logical reasoning for mor... read more
Demystifying Higher-Order Graph Neural Networks.
IEEE transactions on pattern analysis and machine intelligence
Mar 1, 2026
Higher-order graph neural networks (HOGNNs) and the related architectures from Topological Deep Learning are an important class of GNN models that harness polyadic relations between vertices beyond plain edges. They have been used to eliminate issues... read more
Self-Supervised Text-Vision Alignment for Automated Brain MRI Abnormality Detection: A Multicenter Study (ALIGN Study).
Radiology. Artificial intelligence
Mar 1, 2026
Purpose To develop a self-supervised text-vision framework to detect abnormalities on brain MRI scans by leveraging free-text neuroradiology reports, eliminating the need for expert-labeled training datasets. Materials and Methods This retrospective ... read more
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