The rapid development of precision medicine in recent years has started to challenge
diagnostic pathology with respect to its ability to analyze histological images and …

Recent progress in engineering highly promising biocatalysts has increasingly involved
machine learning methods. These methods leverage existing experimental and simulation …

Explainable artificial intelligence (XAI) methods are portrayed as a remedy for debugging
and trusting statistical and deep learning models, as well as interpreting their predictions …

Artificial intelligence (AI) systems utilizing deep neural networks and machine learning (ML)
algorithms are widely used for solving critical problems in bioinformatics, biomedical …

The current move towards digital pathology enables pathologists to use artificial intelligence
(AI)‐based computer programmes for the advanced analysis of whole slide images …

Decision trees (DTs) epitomize the ideal of interpretability of machine learning (ML) models.
The interpretability of decision trees motivates explainability approaches by so-called …

The significant proliferation of AI-empowered systems and machine learning (ML) across
various examined domains underscores the vital necessity for comprehensive and …

The last decade witnessed an ever-increasing stream of successes in Machine Learning
(ML). These successes offer clear evidence that ML is bound to become pervasive in a wide …

Medical and dental artificial intelligence (AI) require the trust of both users and recipients of
the AI to enhance implementation, acceptability, reach, and maintenance. Standardization is …

In this paper, we present a novel Artificial Intelligence (AI)-empowered system that enhances
large language models and other machine learning tools with rules to provide primary care …