Artificial Intelligence Medical Compendium
Explore the latest research on artificial intelligence and machine learning in medicine.
Showing 20,491 to 20,500 of 215,962 articles
Computational Model for Predicting Optimal Clinical Intervention in Pre-Operative Neonates with Transposition of the Great Arteries.
Cardiovascular engineering and technology
May 11, 2026
PURPOSE: Transposition of the Great Arteries (TGA) is a congenital heart defect characterized by the abnormal positioning of the pulmonary artery over the left ventricle and aorta over the right ventricle. Systemic oxygen delivery, therefore, is depe... read more
The evolving global landscape of first-in-class oncology drug innovation.
Signal transduction and targeted therapy
May 11, 2026
First-in-class (FIC) oncology drugs-defined by their novel mechanisms of action or targeting of previously unaddressed molecular targets-have emerged as a leading force in cancer therapeutic innovation. In this Review, we delineate the global landsca... read more
Global patterns of urban heat shaped by climate and morphology.
Nature communications
May 11, 2026
Urban morphology and background climate are evolving drivers of the urban heat island (UHI) effect, yet the thermal influence of surrounding urban structure and its coupling with climate remain elusive. Here, we show that climate and morphology joint... read more
Direct carbapenemase typing from disc diffusion antibiograms with MALCA (MAchine Learning CArbapenemase).
Nature communications
May 11, 2026
Carbapenemase-producing Enterobacterales (CPE) present limited therapeutic options. Optimal treatment requires identifying the carbapenemase type, often requiring confirmatory testing beyond routine susceptibility results. We develop MALCA, a machine... read more
Interpretable machine learning for predicting EUR of shale gas wells in the Weiyuan block.
Scientific reports
May 11, 2026
For shale gas development, it is essential to clarify the main controlling factors of EUR and realize its accurate prediction. Based on data from 123 wells in the Weiyuan block, this study combines Pearson correlation analysis, RF-RFE algorithm, and ... read more
A novel hybrid supervised machine learning model with metaheuristic optimization algorithm for prediction of driver concentration levels.
Scientific reports
May 11, 2026
The rapid expansion of urban living has led to increased road congestion, posing significant challenges for maintaining driver attention and ensuring road safety. This study investigates advanced machine learning techniques to assess and predict driv... read more
Predicting pro-environmental behavioral intention using interpretable machine learning.
Scientific reports
May 11, 2026
This study employs machine learning techniques to investigate the determinants of pro-environmental behavioral intention (PEBI) using the survey data from the 2021 wave of the Chinese General Social Survey (CGSS). By comparing the predictive performa... read more
Monthly soil temperature modelling across different depths using machine learning algorithms in northeast India.
Scientific reports
May 11, 2026
Soil temperature is one of the most crucial factors for agricultural systems, which affects various hydrogeological processes in soil. Soil temperature is a frequently used variable in machine learning (ML) approaches for modelling those intricate pr... read more
An optimized graph neural network approach for robust and explainable IoT intrusion detection against adversarial attacks.
Scientific reports
May 11, 2026
The swift incorporation of cutting edge technologies has expanded the range for a potential adversary to conduct adaptive attacks against systems and despite progress in detection, machine learning based security remains vulnerable, highlighting the ... read more
Search-guided regression ensembles for accurate, interpretable, and uncertainty-aware construction cost estimation.
Scientific reports
May 11, 2026
Accurate and interpretable construction cost estimation remains a major challenge due to complex nonlinear dependencies, heterogeneous data distributions, and inherent uncertainty in project parameters. To overcome these limitations, this study propo... read more
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