Artificial Intelligence Medical Compendium

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

Showing 22,471 to 22,480 of 216,842 articles

Generation of contrast-enhanced cardiac MRI from contrast-free scans: a multi-center, multi-manufacturer study.

European radiology
BACKGROUND: Late gadolinium enhancement (LGE) cardiac magnetic resonance imaging (MRI) is regarded as the non-invasive gold standard for myocardial tissue characterization. However, its reliance on gadolinium-based contrast agents limits its applicab... read more 

Raltegravir Plasma Exposure: A Machine Learning-Based Model for its Prediction Using Limited Sampling Strategy.

The AAPS journal
Recent studies have applied machine learning (ML)-based limited sampling strategies (LSS) to predict drug exposure (AUC), achieving low prediction error and performance comparable to or better than multiple linear regression and population pharmacoki... read more 

De-risking Biopharma Asset Acquisition: Towards a Quantitative Framework for Strategic Decision-making.

The AAPS journal
The impending patent cliff projected between 2028-2030 poses significant commercial and strategic challenges for innovative pharmaceutical and biotechnology companies. To sustain growth and maintain competitive positioning, organizations are increasi... read more 

Multidimensional immune ecological subtyping identifies RUNX1 as a prognostic factor in uveal melanoma.

Discover oncology
Uveal melanoma (UVM) is an aggressive intraocular malignancy with a high risk of metastasis but few effective therapies. However, current molecular classification systems do not completely reflect the immune-stromal interactions underlying tumor prog... read more 

S-MEOD: A Novel Evaluation Metric for Frame-Based Medical Object Detection.

Journal of imaging informatics in medicine
Traditional metrics such as precision, recall, mean Average Precision (mAP), and F-score are widely used to evaluate object detection models. However, in some frame-based medical scenarios, these metrics often fail to capture the true effectiveness o... read more 

Spinal Cord Radiomics-Driven Machine Learning Predicts Meaningful Clinical Improvement After Surgery for Degenerative Cervical Myelopathy: A Pilot Study.

Journal of imaging informatics in medicine
A prospective observational cohort study. To determine whether machine learning models using radiomic features derived from preoperative MRI, clinical variables, or their combination can predict achievement of the minimum clinically important differe... read more 

Automated detection of pediatric forearm fractures in X-ray images using deep learning.

Radiological physics and technology
Children's bones are more elastic and have a thicker periosteum than those of adults, resulting in subtle, incomplete fractures. Diagnosis based on plain radiographs alone can be challenging. The shortage of pediatric radiologists compounds this diff... read more 

Chordless cycle filtrations for dimensionality detection in complex networks via topological data analysis.

Nature communications
Many complex networks, ranging from social to biological systems, exhibit structural patterns consistent with an underlying hyperbolic geometry. Revealing the dimensionality of this latent space can disentangle the structural complexity of communitie... read more 

Enabling DCIS subtyping: leveraging foundation models for robust grading and molecular biomarker scoring.

NPJ breast cancer
Ductal Carcinoma In Situ (DCIS) is a non-obligate precursor of invasive breast cancer. Due to a lack of reliable prognostic markers, nearly all women with DCIS undergo intensive treatment-often unnecessarily. The LORD trial addresses this by offering... read more 

IoT-Enhanced virtual power plants with edge computing and blockchain security for sustainable smart grid management.

Scientific reports
This paper introduces a novel IoT-Enhanced Virtual Power Plant (VPP) framework that integrates edge-fog computing, blockchain-secured communication, and AI-driven market mechanisms to optimize energy management in smart grids. The proposed system add... read more