Results 21 to 30 of about 157,570 (268)

Detection and Classification Method for Early-Stage Colorectal Cancer Using Dyadic Wavelet Packet Transform

IEEE Access
Incorporating deep learning into computer-aided medical diagnosis has led to significant advancements. However, a major challenge remains in interpreting deep learning models, especially in identifying the features critical for diagnosis.
Daigo Takano, Hajime Omura, Teruya Minamoto   +2 more
doaj   +1 more source

Interpretable Model-Agnostic Explanations Based on Feature Relationships for High-Performance Computing

Axioms, 2023
In the explainable artificial intelligence (XAI) field, an algorithm or a tool can help people understand how a model makes a decision. And this can help to select important features to reduce computational costs to realize high-performance computing ...
Zhouyuan Chen, Zhichao Lian, Zhe Xu
doaj   +1 more source

Health‐Related Social Needs in Children With Sickle Cell Disease Are Associated With Worse Health‐Related Quality of Life

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Children with sickle cell disease (SCD) face multiple acute and chronic medical complications that may impact their quality of life as reported by patients themselves. Health‐related social needs (HRSNs), such as food and housing insecurity, are common in people with SCD, but the association between HRSNs and patient‐reported ...
Sarah J. Marks, Molly Sonenklar, Cerelia Donald, Cecelia Valrie, Wally Smith, India Sisler   +5 more
wiley   +1 more source

Towards Explainable Pedestrian Behavior Prediction: A Neuro-Symbolic Framework for Autonomous Driving

Applied Sciences
In the context of autonomous driving, predicting pedestrian behavior is a critical component for enhancing road safety. Currently, the focus of such predictions extends beyond accuracy and reliability, placing increasing emphasis on the explainability ...
Angie Nataly Melo Castillo, Carlota Salinas Maldonado, Miguel Ángel Sotelo   +2 more
doaj   +1 more source

Kolmogorov–Arnold Networks for System Identification of First- and Second-Order Dynamic Systems

Engineering Proceedings
System identification—originating in the 1950s from statistical theory—has since developed a wealth of algorithms, insights, and practical expertise.
Lily Chiparova, Vasil Popov
doaj   +1 more source

Are Fertility Preservation Procedures Before Gonadotoxic Therapy and Hematopoietic Stem Cell Transplantation Feasible and Safe in Very Young Children? A Retrospective Cohort Study

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Fertility preservation (FP) is increasingly integrated into the care of pediatric patients exposed to gonadotoxic therapy or conditioning for hematopoietic stem cell transplantation (HSCT), yet perioperative data in infants and toddlers remain scarce.
Kerstin Saalabian, Yannick Braun, Till‐Martin Theilen, Anke Barnbrock, Theresa Rohm, Fabienne Hammant, Nicole Sänger, Aynura Abbasova‐Semiz, Jan‐Henning Klusmann, Thomas Klingebiel, Udo Rolle, Peter Bader, Henning C. Fiegel, Andrea Jarisch   +13 more
wiley   +1 more source

Eye Tracking-Enhanced Deep Learning for Medical Image Analysis: A Systematic Review on Data Efficiency, Interpretability, and Multimodal Integration

Bioengineering
Deep learning (DL) has revolutionized medical image analysis (MIA), enabling early anomaly detection, precise lesion segmentation, and automated disease classification.
Jiangxia Duan, Meiwei Zhang, Minghui Song, Xiaopan Xu, Hongbing Lu   +4 more
doaj   +1 more source

Central Nervous System Neuroblastoma, FOXR2‐Activated: A Pooled Analysis of Published Clinical Outcomes

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Central nervous system (CNS) neuroblastoma, FOXR2‐activated, is a recently recognized entity in the WHO CNS5 classification, defined by activation of the FOXR2 transcription factor and unique histopathological features. This review synthesizes available literature and pooled clinical data, providing insight into demographics ...
Sudarshawn Damodharan, Mohamed S. Abdelbaki   +1 more
wiley   +1 more source

Investigating the Performance of the Attention Mechanism and the Interpretability in the Concrete Strength Prediction Model

Buildings
To address the limitations of traditional models in capturing complex features for concrete strength prediction, this study proposes a hybrid deep learning approach that integrates multiple attention mechanisms with gated recurrent units (GRU).
Ziang Jia, Noor Azline Mohd Nasir, Nabilah Abu Bakar   +2 more
doaj   +1 more source

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