Results 171 to 180 of about 2,085,409 (278)

Unveiling the Algorithm: The Role of Explainable Artificial Intelligence in Modern Surgery

Artificial Intelligence (AI) is rapidly transforming surgical care by enabling more accurate diagnosis and risk prediction, personalized decision-making, real-time intraoperative support, and postoperative management.
João Fonseca, Maria Gabriela O. Fernandes, Miguel Mascarenhas, Sara Lopes, Fernandes, Maria Gabriela O., Fonseca, Jo\ue3o, Lopes, Sara, Leite-Moreira, Adelino F., Adelino F. Leite-Moreira, Mascarenhas, Miguel   +9 more
core   +1 more source

Tailoring Microstructure and Hardness in Maraging 300 Steel via 2.4 wt.% Niobium Addition and Controlled Aging Treatments

steel research international, EarlyView.
High Nb (2.4 wt.%) addition to Maraging 300 steel drives lattice distortion and nanoscale Nb–Mo‐rich precipitation, confirmed by energy‐dispersive X‐ray spectroscopy mapping (Mo ~5.4 wt.%, Nb ~2.5 wt.%). Nanoindentation reveals strong matrix hardening (H >4.8 GPa) at 480°C aging, while 560°C induces ~1.92 vol.% reverted austenite, enabling tunable ...
Laylla Sharon B. Peixoto, Mohammad Masoumi, Luís Henrique N. de Lima, Marcos Natan da Silva Lima, Luis Flávio Gaspar Herculano, Isabel Ferreira de Barros, Geronimo Perez, Maria Vittoria Moraschini Reis, Hamilton Ferreira Gome Abreu, Marcelo J. Gomes da Silva   +9 more
wiley   +1 more source

Explainable Artificial Intelligence (XAI) for Deep Learning Based Medical Imaging Classification. [PDF]

J Imaging, 2023
Ghnemat R, Alodibat S, Abu Al-Haija Q.
europepmc   +1 more source

Understanding and Mitigating Bias From Artificial Intelligence in Otolaryngology: A State‐of‐the‐Art Review

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Objective To provide an overview of potential biases resulting from the utilization of artificial intelligence (AI) in otolaryngology and techniques to mitigate them. Data Sources Literature review and expert opinion. Conclusions AI promises to fundamentally transform medicine.
Matthew T. Ryan, David A. Gudis
wiley   +1 more source

Artificial Intelligence in Voice Disorders: Current Landscape, Emerging Applications and Future Directions

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
ABSTRACT Objective To provide a comprehensive review of the current landscape of artificial intelligence (AI) applications in voice disorder, with emphasis on emerging applications, limitations, and future directions for clinical integration. Methods Literature review.
Rachel B. Kutler, Anaïs Rameau
wiley   +1 more source

Explainable Artificial Intelligence in the Field of Drug Research

Drug Design, Development and Therapy
Qingyao Ding,1 Rufan Yao,1 Yue Bai,1 Limu Da,1 Yujiang Wang,2 Rongwu Xiang,1,3,4 Xiwei Jiang,1 Fei Zhai1 1Faculty of Medical Devices, Shenyang Pharmaceutical University, Shenyang, Liaoning Province, People’s Republic of China; 2Department of Internal ...
Ding Q, Yao R, Bai Y, Da L, Wang Y, Xiang R, Jiang X, Zhai F   +7 more
doaj  

Dissecting Glioma Heterogeneity: A Deep Hybrid Graph Convolutional Network With Hinge Attention for Causal‐Effect Explainability

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Brain tumour classification is a critical task in medical imaging that requires accurate and interpretable solutions to assist in clinical decision‐making. In this paper, we present GraphConvNet‐X, a novel hybrid model that integrates convolutional neural networks (CNNs) for spatial feature extraction with graph neural networks (GNNs) that ...
Sultanul Arifeen Hamim, Mubasshar U. I. Tamim, S. M. Hasan Mahmud, M. F. Mridha, Zeyar Aung   +4 more
wiley   +1 more source

Spatial flood susceptibility mapping using an explainable artificial intelligence (XAI) model

Geoscience Frontiers, 2023
B. Pradhan, Saro Lee, Abhirup Dikshit, Hyesu Kim   +3 more
semanticscholar   +1 more source

Theia: An end‐to‐end edge‐AI mobile framework for high‐throughput field phenotyping and on‐device geometric morphometrics

Methods in Ecology and Evolution, EarlyView.
Abstract Geometric morphometrics (GM) is widely used to study phenotypic variation in ecological and evolutionary research, but the throughput of manual landmark digitization limits how large morphometric datasets can practically become, especially in field studies that would benefit from rapid on‐site feedback.
Cristobal Bragagnolo, Andrés Ferreira‐Rodríguez, Mohamed Abdelaziz, A. Jesús Muñoz‐Pajares   +3 more
wiley   +1 more source

Explainable Artificial Intelligence (XAI) and Molecular Modeling Techniques to Discover Putative HER2 Inhibitors. [PDF]

Int J Mol Sci
Rampogu S, Balasubramaniyam T, Yoon CH, Kim Y, Kubiak JZ, Lee KW.   +5 more
europepmc   +1 more source