Results 91 to 100 of about 1,145,019 (271)
AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley +1 more source
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang +3 more
wiley +1 more source
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker +2 more
wiley +1 more source
IntroductionWhile research in online sports betting is dominated by studies using objective player tracking data from providers to identify risky gambling behavior, basicresearch has identified various putative individual risk factors assumed to underlie
Theresa Wirkus +6 more
doaj +1 more source
Gambling disorder gender analysis: social strain, gender norms, and self-control as risk factors
IntroductionGender differences in problem gambling have attracted much attention in recent gambling literature. However, relatively little is known about how gender norms relate to social strain and self-control in predicting gambling disorder within a ...
Pui Kwan Man
doaj +1 more source
Problem gambling and gaming in elite athletes
Background: High-level sports have been described as a risk situation for mental health problems and substance misuse. This, however, has been sparsely studied for problem gambling, and it is unknown whether problem gaming, corresponding to the tentative
A. Håkansson +2 more
doaj +1 more source
A hybrid Reinforcement Learning–Explainable AI framework integrates SHAP and LIME explanations directly into a Deep Q‐Network inference loop for real‐time ICU decision support. Trained on 18 142 mechanically ventilated stays from the eICU database, the system attains 93.0% decision accuracy, 20% fewer errors than RL alone, and a 91% clinician trust ...
Jannatul Ferdaus Disha +2 more
wiley +1 more source
Comparative Analysis of Model‐Agnostic Explanation Methods in Materials Science
To address the critical lack of explainable artificial intelligence (XAI) benchmarks in materials science, we present a quantitative and qualitative analysis of six XAI methods applied to molecular fingerprints. Our results reveal significant discrepancies in feature importance rankings, demonstrating that the chosen explanation approach introduces ...
Anna Przybyłowska +7 more
wiley +1 more source
Responsible Artificial Intelligence in Courts: A Four‐Test Framework
ABSTRACT A structured framework for responsible AI applications relating to judicial decision‐making and the adjudicative functions of courts requires the satisfaction of multiple context‐specific safeguards. This article proposes a four‐test framework designed to evaluate whether AI systems used in courts operate in accordance with legal, procedural ...
Kwan Yiu Cheng
wiley +1 more source
Accounting for animal health in efficiency analysis: An application to Swedish dairy farms
Abstract Poor animal health is a central concern in modern livestock production. Despite the necessity to incorporate animal health in efficiency analysis, the theoretical and empirical developments are limited on this subject. This article appropriately characterizes the axiomatic properties of animal health within a production framework.
Frederic Ang +3 more
wiley +1 more source

