Results 101 to 110 of about 2,085,409 (278)

Comparative Analysis of Model‐Agnostic Explanation Methods in Materials Science

Advanced Intelligent Systems, EarlyView.
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, Joanna Neubauer, Monika Sztuder, Witold Taisner, Agnieszka Hryniewicka, Julia Kolodziejczyk, Marta Eliza Plonska‐Brzezinska, Dariusz Brzezinski   +7 more
wiley   +1 more source

Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy

Advanced Intelligent Systems, EarlyView.
This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne, Haodong Yao, Liyuan Wu, Yihe Pang, Fazhi Qi, Lina Zhao   +5 more
wiley   +1 more source

GastroNet: A robust attention‐based deep learning and cosine similarity feature selection framework for gastrointestinal disease classification from endoscopic images

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Diseases of the Gastrointestinal (GI) tract significantly affect the quality of human life and have a high fatality rate. Accurate diagnosis of GI diseases plays a pivotal role in healthcare systems. However, processing large amounts of medical image data can be challenging for radiologists and other medical professionals, increasing the risk ...
Muhammad Nouman Noor, Muhammad Nazir, Imran Ashraf, Nouf Abdullah Almujally, Muhammad Aslam, Syeda Fizzah Jilani   +5 more
wiley   +1 more source

AS‐XAI: Self‐Supervised Automatic Semantic Interpretation for CNN

Advanced Intelligent Systems
Explainable artificial intelligence (XAI) aims to develop transparent explanatory approaches for “black‐box” deep learning models. However, it remains difficult for existing methods to achieve the trade‐off of the three key criteria in interpretability ...
Changqi Sun, Hao Xu, Yuntian Chen, Dongxiao Zhang   +3 more
doaj   +1 more source

Navigating AI with pedagogical purpose: Toward an anatomy‐centered framework for AI‐enhanced learning

Anatomical Sciences Education, EarlyView.
Abstract Artificial Intelligence (AI) has emerged as a transformative force in medical education, enabling customized, feedback‐rich, and immersive learning experiences. Anatomy education, as a discipline that is simultaneously visual, spatial, and clinically foundational, occupies a distinctive position within this technological landscape.
Rachel Jayasekhar, Gok Kandasamy
wiley   +1 more source

Explainable human‐in‐the‐loop healthcare image information quality assessment and selection

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Smart healthcare applications cannot be separated from healthcare data analysis and the interactive interpretability between data and model. A human‐in‐the‐loop active learning approach is introduced to reduce the cost of healthcare data labelling by evaluating the information quality of unlabelled medical data and then screening the high ...
Yang Li, Sezai Ercisli
wiley   +1 more source

Bridging the translational gap in clinical nanomedicine: From rational design to clinical reality

BMEMat, EarlyView.
Nanotechnology offers a multi‐faceted approach to modern healthcare, encompassing high‐sensitivity diagnostic imaging, innovative vaccine delivery, and targeted therapeutics. This review explores how these nanomedicine applications address critical challenges in cancer recurrence and the treatment of neurologic and respiratory diseases to combat rising
Ahmed H. Ghonaim, Marwa Ahmed El‐Naka, Wedad M. Nageeb, Atta Ullah Khan, Noura M. Seleem, Aliaa Abdelghafar, Doaa Zamel, Yang Liu, Qigai He, Wentao Li   +9 more
wiley   +1 more source

Effectiveness of Explainable Artificial Intelligence (XAI) Techniques for Improving Human Trust in Machine Learning Models: A Systematic Literature Review

IEEE Access
Most decision-making processes worldwide are increasingly relying on artificial intelligence (AI) algorithms to enhance human welfare. Explainable Artificial Intelligence (XAI) techniques are pivotal in addressing the bottlenecks of utilizing machine ...
In-On Wiratsin, Chaiyong Ragkhitwetsagul
doaj   +1 more source

Artificial Intelligence–Driven and Digital Practices for Circular Business and Finance: Insights for Advancing Hubs for Circularity

Business Strategy and the Environment, EarlyView.
ABSTRACT The emerging concept of Hubs for Circularity (H4Cs) presents an opportunity to create collaborative, self‐sustaining regional industrial ecosystems that drive circular economy transitions at scale. However, the operationalisation of H4Cs faces financial, organisational and data‐driven challenges.
Aditya Tripathi, Marcos R. Machado, Laura Spierdijk, Devrim Murat Yazan   +3 more
wiley   +1 more source

Editorial: From Explainable Artificial Intelligence (xAI) to Understandable Artificial Intelligence (uAI) [PDF]

In this editorial, we argue that the artificial intelligence (AI) community needs to escape the trap of explainable artificial intelligence (xAI) by growing more research on understandable artificial intelligence (uAI).
Alexander Gegov (24044517), Uzay Kaymak (6278192), Keeley Crockett (23882010), Joao Miguel C Sousa (24044520), Hussein Abbass (21314999), Jonathan Garibaldi (6594977)   +5 more
core   +2 more sources