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Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

Ebtisam AlJalaud, Manar Hosny • Mathematics (2024)

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior...

DOAJ Open Access (DOAJ) DOI: 10.3390/math12233727

Investigations on Rockmass Structure Characteristics and Mechanical Mining Efficiency and Economics in the Jinchuan No. 3 Mine With Hard Rock

Jian Zhao, Dan Huang, Daming Zhu, Mingyue Wang et al. • Advances in Civil Engineering (2026)

Geomechanical characterization is crucial for assessing the feasibility of the mechanical construction method in geotechnical engineering, which is a construction method that neither uses explosives nor involves blasting operations. But for...

DOAJ Open Access (DOAJ) DOI: 10.1155/adce/2598677

Artificial Intelligence for Intraoperative Guidance

Amin Madani, Babak Namazi, Maria S. Altieri, Daniel A. Hashimoto et al. • Annals of Surgery (2020)

OBJECTIVE: The aim of this study was to develop and evaluate the performance of artificial intelligence (AI) models that can identify safe and dangerous zones of dissection, and anatomical landmarks during laparoscopic cholecystectomy (LC)....

OPENALEX Open Access DOI: https://doi.org/10.1097/sla.0000000000004594 PMC: 8186165

An automated deep learning framework for brain tumor classification using MRI imagery

Muhammad Aamir, Ziaur Rahman, Uzair Aslam Bhatti, Waheed Ahmed Abro et al. • Scientific Reports (2025)

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-02209-2

AI-driven data fusion modeling for enhanced prediction of mixed-mode I/III fracture toughness

Anantaya Timtong, Atthaphon Ariyarit, Wanwanut Boongsood, Prasert Aengchuan et al. • Results in Engineering (2024)

This research evaluates the use of artificial intelligence to enhance the accuracy of predictions for mixed-mode I/III fracture toughness in polymethyl methacrylate . Traditionally, assessing fracture toughness relies heavily on destructive...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.rineng.2024.103289

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Song Zeng, Xin-Lu Wang, Hua Yang • Military Medical Research (2024)

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40779-024-00580-1

The Effects of Large Language Models on the Generation of Multiple-choice Questions in Medical Education: A Scoping Review

Baleegh Elsir Ahmed Mohammed, Tanzeel Elsir Ahmed Mohammed, Anthony Paul Breitbach • Sudan Journal of Medical Sciences (2026)

Background: Constructing high-quality multiple-choice questions (MCQs) is critical yet resource-intensive in medical education. Large language models (LLMs), such as ChatGPT, have become promising tools for generating MCQs in medical educat...

DOAJ Open Access (DOAJ) DOI: 10.18502/sjms.v21i2.19868

A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography

Changhee Yun, Bomi Eom, Sungjun Park, Chanho Kim et al. • Sensors (2023)

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delica...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23052864

Artificial intelligence in glaucoma

Chengjie Zheng, Thomas V. Johnson, Aakriti Garg Shukla, Michael Vincent Boland • Current Opinion in Ophthalmology (2018)

PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making, and artificial intelligence methods have recently demonstrated significant advances in medicine. We therefore provide an overview of curren...

OPENALEX DOI: https://doi.org/10.1097/icu.0000000000000552

Uncertainty in artificial intelligence

Simon Parsons • The Knowledge Engineering Review (1994)

The first conference on Uncertainty in Artificial Intelligence was held in 1985 by a group of people who felt that their views on the use of probability theory were not receiving a fair hearing from the rest of the Al community. At the time...

OPENALEX Open Access DOI: https://doi.org/10.1017/s0269888900006597

Artificial Intelligence with Uncertainty

Deyi Li, Yi Du • CRC Press eBooks (2017)

This book develops a framework that shows how uncertainty in Artificial Intelligence (AI) expands and generalizes traditional AI. It explores the uncertainties of knowledge and intelligence. The authors focus on the importance of natural la...

OPENALEX DOI: https://doi.org/10.1201/9781315366951