Results 41 to 50 of about 424,704 (329)

Explainable Machine Learning for Scientific Insights and Discoveries

IEEE Access, 2020
Machine learning methods have been remarkably successful for a wide range of application areas in the extraction of essential information from data. An exciting and relatively recent development is the uptake of machine learning in the natural sciences ...
Ribana Roscher, Bastian Bohn, Marco F. Duarte, Jochen Garcke   +3 more
doaj   +1 more source

Survival Outcomes and Complications Among Canadian Children With Retinoblastoma: A Population‐Based Report From CYP‐C

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Retinoblastoma (RB) is the most common pediatric ocular cancer, yet population‐based data on survival and risk factors remain limited. This study aimed to describe survival in a large national RB cohort and identify predictors of death and complications.
Samuel Sassine, Ofélie Trudeau‐Ferrin, Caroline Laverdière, Patrick Hamel, Rosanne Superstein, Bénédicte Koukoui, Carole Provost, Paul C. Nathan, Vijay Ramaswamy, Furqan Shaikh, Brenda Gallie, Ashwin Mallipatna, Stephanie Kletke, Helen Dimaras, Hallie Coltin   +14 more
wiley   +1 more source

Geometric Reasoning in the Embedding Space

Machine Learning and Knowledge Extraction
While neural networks can solve complex geometric problems, as demonstrated by systems like AlphaGeometry, we have limited understanding of how they internally represent and reason about spatial relationships.
David Mojžíšek, Jan Hůla, Jiří Janeček, David Herel, Mikoláš Janota   +4 more
doaj   +1 more source

A Review of Explainable Artificial Intelligence from the Perspectives of Challenges and Opportunities

Algorithms
The widespread adoption of Artificial Intelligence (AI) in critical domains, such as healthcare, finance, law, and autonomous systems, has brought unprecedented societal benefits.
Sami Kabir, Mohammad Shahadat Hossain, Karl Andersson   +2 more
doaj   +1 more source

Adherence to Protocol Recommendations for Children With Wilms Tumour in Two Consecutive Studies in the United Kingdom and Ireland—Does Variation Matter?

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background and Aims Wilms tumour (WT) has excellent event‐free and overall survival (OS). However, small differences exist between countries participating in the same international study. This led us to examine variation in adherence to protocol recommendations as a potential contributing factor.
Suzanne Tugnait, R. Al‐Saadi, A. Lopez‐Cortes, K. Dzhuma, M. Oostveen, J. Brok, S. Irtan, M. Weeks, J. Bate, S. Baker, R. Williams, M. Powis, D. Saunders, O. Olsen, T. Watson, S. Shelmerdine, S. Vaidya, L. Howell, C. Duncan, G. M. Vujanic, C. Stiller, G. P. Balchin, T. Chowdhury, K. Pritchard‐Jones   +23 more
wiley   +1 more source

Fuzzy-DogNet: A Lightweight and Interpretable Deep Unstructured Neuro-Fuzzy System Based on Band-Pass Filters for Traffic Sign Recognition

IEEE Access
Traffic Sign Recognition (TSR) plays a critical role in autonomous driving and advanced driver-assistance systems, necessitating accurate and efficient recognition under real-world constraints.
Sadra Berangi, Mohammad Mahdi Parchamijalal, Armin Salimi-Badr   +2 more
doaj   +1 more source

Prediction of red blood cell transfusion after orthopedic surgery using an interpretable machine learning framework

Frontiers in Surgery, 2023
ObjectivePostoperative red blood cell (RBC) transfusion is widely used during the perioperative period but is often associated with a high risk of infection and complications.
Yifeng Chen, Xiaoyu Cai, Zicheng Cao, Jie Lin, Wenyu Huang, Yuan Zhuang, Lehan Xiao, Xiaozhen Guan, Ying Wang, Xingqiu Xia, Feng Jiao, Xiangjun Du, Guozhi Jiang, Guozhi Jiang, Deqing Wang   +14 more
doaj   +1 more source

Evaluating the Utility of Paired Tumor and Germline Targeted DNA Sequencing for Pediatric Oncology Patients: A Single Institution Report

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Objective To evaluate the diagnostic yield and utility of universal paired tumor–normal multigene panel sequencing in newly diagnosed pediatric solid and central nervous system (CNS) tumor patients and to compare the detection of germline pathogenic/likely pathogenic variants (PV/LPVs) against established clinical referral criteria for cancer ...
Natalie Waligorski, Rebecca Ronsley, Shannon M. Stasi, Jeffrey Stevens, Erin R. Rudzinski, Christina M. Lockwood, Sarah E. S. Leary, Bonnie L. Cole, Michelle A. Ting, Vera Paulson   +9 more
wiley   +1 more source

Signal Processing in the Retina: Interpretable Graph Classifier to Predict Ganglion Cell Responses

IEEE Open Journal of Signal Processing
It is a popular hypothesis in neuroscience that ganglion cells in the retina are activated by selectively detecting visual features in an observed scene.
Yasaman Parhizkar, Gene Cheung, Andrew W. Eckford   +2 more
doaj   +1 more source

NN-Poly: Approximating common neural networks with Taylor polynomials to imbue dynamical system constraints

Frontiers in Robotics and AI, 2022
Recent advances in deep learning have bolstered our ability to forecast the evolution of dynamical systems, but common neural networks do not adhere to physical laws, critical information that could lead to sounder state predictions.
Frances Zhu, Dongheng Jing, Frederick Leve, Silvia Ferrari   +3 more
doaj   +1 more source