Aquila Optimizer (AO) is a well-known nature-inspired optimization algorithm (NIOA) that
was created in 2021 based on the prey grabbing behavior of Aquila. AO is a population …

Radiomics is the extraction of predefined mathematic features from medical images for
predicting variables of clinical interest. Recent research has demonstrated that radiomics …

Deep learning models have revolutionized numerous fields, yet their decision-making
processes often remain opaque, earning them the characterization of “black-box” models …

In the evolving landscape of medical imaging, the escalating need for deep-learning
methods takes center stage, offering the capability to autonomously acquire abstract data …

Artificial intelligence technologies such as machine learning and deep learning employ
techniques to anticipate results more effectively without human involvement. Since AI …

Abstract Machine learning (ML) has achieved substantial success in performing healthcare
tasks in which the configuration of every part of the ML pipeline relies heavily on technical …

In this study, we present a novel approach to enhancing the interpretability of medical image
classification by integrating formal concept analysis (FCA) with convolutional neural …

Abstract The Aquila Optimization (AO) algorithm is a newly established swarm-based
method that mimics the hunting behavior of Aquila birds in nature. However, in complex …

The healthcare sector has advanced significantly as a result of the ability of artificial
intelligence (AI) to solve cognitive problems that once required human intelligence. As …

Background: The interpretability and explainability of machine learning (ML) and artificial
intelligence systems are critical for generating trust in their outcomes in fields such as …