Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes?

Biomedicines, Journal Year: 2025, Volume and Issue: 13(4), P. 836 - 836

Published: March 31, 2025

Pancreatic cancer is one of the most lethal neoplasms. Despite considerable research conducted in recent decades, not much has been achieved to improve its survival rate. That may stem from lack effective screening strategies increased pancreatic risk groups. One population that be appropriate for new-onset diabetes (NOD) patients. Such a conclusion stems fact can cause several months before diagnosis. The widely used tool this population, ENDPAC (Enriching New-Onset Diabetes Cancer) model, satisfactory results validation trials. This provoked first attempts at using artificial intelligence (AI) create larger, multi-parameter models could better identify at-risk which would suitable screening. shown by authors these trials seem promising. Nonetheless, number publications limited, and downfalls AI are well highlighted. narrative review presents summary previous publications, advancements feasible solutions patients with NOD cancer.

Language: Английский

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Explaining basketball game performance with SHAP: insights from Chinese Basketball Association

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 21, 2025

This study explores the Key Performance Indicators (KPIs) influencing game outcomes of Chinese Basketball Association (CBA). Utilizing data from 4100 games across 10 CBA seasons (2013-2023), this constructs outcome prediction models using seven machine learning algorithms, including XGBoost, LightGBM, Decision Tree, Random Forest, Support Vector Machines, Logistic Regression, and K-Nearest Neighbors. The SHapley Additive exPlanation (SHAP) method is applied to explain optimal model analyze KPIs. findings are as follows: (1) XGBoost demonstrates excellent performance in predicting outcomes. (2) eFG%, 3P%, 2P%, ORB%, DRB, TOV% key indicators (3) There a tendency for offensive play over defensive strategies playoffs. combined methodology SHAP analysis not only exhibits superior but also strong explainability. It effectively reflects relationship between data, providing scientific basis enhancing professional basketball performance.

Language: Английский

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RPCA with Log-Schatten Norm and Adaptive Histogram Equalization for Medical Imaging

International Journal of Statistics in Medical Research, Journal Year: 2025, Volume and Issue: 14, P. 274 - 288

Published: May 3, 2025

Medical imaging, especially cancer and retinal fundus analysis, is often compromised by artifacts heavy noise artifact, which can hinder accurate diagnosis. Existing low-rank sparse component methods, such as RPCA with the conventional nuclear norm, assume uniform singular value weights, may not hold true due to variations in images. We recently developed log-weighted addresses some of these issues but still relies on weight selection, potentially introducing bias. To overcome limitations, we propose a novel method that integrates Log-Schatten Norm (LSN) Adaptive Histogram Equalization (AHE) for medical imaging clinical purposes. The improves penalization structure preservation, while AHE enhances contrast reduces noise. formulated an optimization problem solved using Alternating Direction Method Multipliers (ADMM). Experimental results publicly available image datasets demonstrate our outperforms existing methods enhancing overall quality, making it promising tool applications.

Language: Английский

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From Algorithms to Insight: The Transformative Power of Artificial Intelligence and Machine Learning in Urological Cancer Research

Current Oncology, Journal Year: 2025, Volume and Issue: 32(5), P. 277 - 277

Published: May 14, 2025

As we advance into a new era of oncological science, artificial intelligence (AI) is no longer peripheral tool—it central agent change [...]

Language: Английский

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