Artificial Intelligence Medical Compendium

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

Showing 48,741 to 48,750 of 224,513 articles

MedClarify: An information-seeking AI agent for medical diagnosis with case-specific follow-up questions

arXiv Feb 19, 2026
Large language models (LLMs) are increasingly used for diagnostic tasks in medicine. In clinical practice, the correct diagnosis can rarely be immediately inferred from the initial patient presentation alone. Rather, reaching a diagnosis often involv... read more 
Artificial Intelligence cs.LG

Attachment Anchors: A Novel Framework for Laparoscopic Grasping Point Prediction in Colorectal Surgery

arXiv Feb 19, 2026
Accurate grasping point prediction is a key challenge for autonomous tissue manipulation in minimally invasive surgery, particularly in complex and variable procedures such as colorectal interventions. Due to their complexity and prolonged duration, ... read more 
Computer Vision and Pattern Recognition

The Sound of Death: Deep Learning Reveals Vascular Damage from Carotid Ultrasound

arXiv Feb 19, 2026
Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, yet early risk detection is often limited by available diagnostics. Carotid ultrasound, a non-invasive and widely accessible modality, encodes rich structural and hemodyn... read more 
Machine Learning cs.CV

Leveraging Contrastive Learning for a Similarity-Guided Tampered Document Data Generation Pipeline

arXiv Feb 19, 2026
Detecting tampered text in document images is a challenging task due to data scarcity. To address this, previous work has attempted to generate tampered documents using rule-based methods. However, the resulting documents often suffer from limited va... read more 
Computer Vision and Pattern Recognition

SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework

arXiv Feb 19, 2026
Comparative analysis of adaptive immune repertoires at population scale is hampered by two practical bottlenecks: the near-quadratic cost of pairwise affinity evaluations and dataset imbalances that obscure clinically important minority clonotypes. W... read more 
Machine Learning cs.AI

Polaffini: A feature-based approach for robust affine and polyaffine image registration

arXiv Feb 19, 2026
In this work we present Polaffini, a robust and versatile framework for anatomically grounded registration. Medical image registration is dominated by intensity-based registration methods that rely on surrogate measures of alignment quality. In contr... read more 
Computer Vision and Pattern Recognition

Partial Optimality in the Preordering Problem

arXiv Feb 19, 2026
Preordering is a generalization of clustering and partial ordering with applications in bioinformatics and social network analysis. Given a finite set $V$ and a value $c_{ab} \in \mathbb{R}$ for every ordered pair $ab$ of elements of $V$, the preorde... read more 
Discrete Mathematics cs.DS cs.LG

Application and Evaluation of the Common Circles Method

arXiv Feb 19, 2026
We investigate the application of the common circle method for estimating sample motion in optical diffraction tomography (ODT) of sub-millimeter sized biological tissue. When samples are confined via contact-free acoustical force fields, their motio... read more 
Numerical Analysis cs.CV

Training-free Graph-based Imputation of Missing Modalities in Multimodal Recommendation

arXiv Feb 19, 2026
Multimodal recommender systems (RSs) represent items in the catalog through multimodal data (e.g., product images and descriptions) that, in some cases, might be noisy or (even worse) missing. In those scenarios, the common practice is to drop items ... read more 
Information Retrieval

A feature-stable and explainable machine learning framework for trustworthy decision-making under incomplete clinical data

arXiv Feb 19, 2026
Machine learning models are increasingly applied to biomedical data, yet their adoption in high stakes domains remains limited by poor robustness, limited interpretability, and instability of learned features under realistic data perturbations, such ... read more 
Machine Learning cs.AI
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