Artificial Intelligence Medical Compendium

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

Showing 1,261 to 1,270 of 213,568 articles

Physics-informed multi-task learning for permeability prediction and probabilistic HFU modeling: a case study from the Lower Bahariya Reservoir, Shahd SE field Egypt.

Scientific reports
Accurate permeability prediction is essential for reliable reservoir characterization and simulation, yet remains challenging due to complex nonlinear relationships and subsurface heterogeneity. Conventional hydraulic flow unit (HFU) methods rely on ... read more 

Adaptive test-time augmentation via KL-regularized reinforcement learning for robust visual inference.

Scientific reports
Deep neural networks often suffer significant accuracy degradation when exposed to real-world image corruptions and distribution shifts. To overcome the limitations of fixed, input-agnostic test-time augmentation (TTA), an adaptive framework is propo... read more 

Symbolic and domain-generalized machine learning for interpretable solubility modeling in supercritical CO₂.

Scientific reports
Accurate prediction of drug solubility in supercritical CO₂ remains challenging due to the limited generalizability of compound-specific correlations and the black-box nature of most machine learning models. This study proposes a domain-aware symboli... read more 

A clinically interpretable model for predicting pharyngocutaneous fistula after total laryngectomy.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
BACKGROUND: Pharyngocutaneous fistula (PCF) is a frequent complication following total laryngectomy. While various risk models exist, their practical utility is often limited by poor calibration and a lack of guidance on modifiable risk factors. This... read more 

Comprehensive evaluation of angiogenesis-associated genes in papillary thyroid cancer using bulk RNA and single-cell sequencing data.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
OBJECTIVE: The objective of this study is to explore the expression patterns of angiogenesis-related genes in papillary thyroid cancer (PTC) to enhance understanding of the molecular mechanisms underlying angiogenesis in this malignancy. The findings... read more 

Real-world diagnostic and management decisions in rhinology by a large language model: a retrospective study.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
BACKGROUND: Large language models (LLMs) have shown promising performance in medical knowledge assessment; however, their capacity to assist real-world clinical decision-making in rhinology, particularly when integrating clinical, endoscopic, and rad... read more 

Digital twins: a call for an under-developed tool in otolaryngology-head and neck surgery.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
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ChatGPT vs. multidisciplinary team decisions in auditory implantation: a concordance analysis of implant type and side selection.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
INTRODUCTION: Auditory implantation is a standard rehabilitation strategy for patients with severe hearing loss, and candidacy determination requires a multidisciplinary, multidimensional evaluation. With the increasing clinical use of artificial int... read more 

Graph-augmented transformer networks and explainable AI for economic impact forecasting in disrupted supply chains.

Scientific reports
This study proposes a hybrid AI model which integrates Graph Neural Networks and Transformer models to predict the economic consequence of the disruption of the supply chains with unprecedented accuracy (MAPE: 3.7%). The framework is based on multi-d... read more 

Training Deep Learning Based Dynamic MR Image Reconstruction Using Synthetic Fractals.

Magnetic resonance in medicine
PURPOSE: To investigate whether synthetically generated fractal data can be used to train deep learning (DL) models for dynamic MRI reconstruction, thereby avoiding the privacy, licensing, and availability limitations associated with cardiac MR train... read more