Imagen de Portada

Opening the black box of deep learning: Validating the statistical association between explainable artificial intelligence (XAI) and clinical domain knowledge in fundus image-based glaucoma diagnosis

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Yuan, Han, Kang, Lican, Li, Yong
Formato:	Preprint
Publicado:	2025
Materias:	Computer Vision and Pattern Recognition
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Human‐in‐the‐loop machine learning for healthcare: Current progress and future opportunities in electronic health records
por: Han Yuan, et al.
Publicado: (2024)

What artificial intelligence can bring us in the diagnosis and progression of glaucoma
por: Sara Ettouri, et al.
Publicado: (2024)

Automated detection of motion artifacts in brain MR images using deep learning and explainable artificial intelligence
por: Jimeno, Marina Manso, et al.
Publicado: (2024)

Explainable artificial intelligence (XAI): from inherent explainability to large language models
por: Mumuni, Fuseini, et al.
Publicado: (2025)

Application of artificial intelligence in glaucoma
por: Ningli Wang
Publicado: (2024)

Deep learning of committor and explainable artificial intelligence analysis for identifying reaction coordinates
por: Mori, Toshifumi, et al.
Publicado: (2026)

MaxGlaViT: A novel lightweight vision transformer-based approach for early diagnosis of glaucoma stages from fundus images
por: Yurdakul, Mustafa, et al.
Publicado: (2025)

Opening the black box of language acquisition
por: Michaud, Jérôme, et al.
Publicado: (2024)

Diagnosis of glaucoma from retinal fundus images using disc localization and sequential DNN model
por: Kamesh Sonti, et al.
Publicado: (2024)

An explainable hybrid deep learning-enabled intelligent fault detection and diagnosis approach for automotive software systems validation
por: Abboush, Mohammad, et al.
Publicado: (2026)

An explainable artificial intelligence‐based approach for reliable damage detection in polymer composite structures using deep learning
por: Muhammad Muzammil Azad, et al.
Publicado: (2024)

Towards consistency of rule-based explainer and black box model -- fusion of rule induction and XAI-based feature importance
por: Kozielski, Michał, et al.
Publicado: (2024)

Model-agnostic explainable artificial intelligence for object detection in image data
por: Moradi, Milad, et al.
Publicado: (2023)

Robust deep learning for eye fundus images: Bridging real and synthetic data for enhancing generalization
por: Oliveira, Guilherme C., et al.
Publicado: (2022)

Digital pathology‐based artificial intelligence algorithms in prostate cancer: inside the ‘black box’
por: Claire M. de la Calle, et al.
Publicado: (2026)

Opening the “black box”: Organizational differences between charter schools and traditional public schools
por: Xin Wei
Publicado: (2014)

Soft-CAM: Making black box models self-explainable for medical image analysis
por: Djoumessi, Kerol, et al.
Publicado: (2025)

Private Virtual Tree Networks for Secure Multi-Tenant Environments Based on the VIRGO Overlay Network
por: Huang, Lican
Publicado: (2025)

sVIRGO: A Scalable Virtual Tree Hierarchical Framework for Distributed Systems
por: Huang, Lican
Publicado: (2026)

Shu Dao: A Calligraphy Score Framework Linking Calligraphy, Music, and Performance
por: Huang, Lican
Publicado: (2026)

Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia
por: Rong‐Xin Guo, et al.
Publicado: (2024)

Effects of explainable artificial intelligence in neurology decision support
por: Grace Y. Gombolay, et al.
Publicado: (2024)

Achieving interpretable machine learning by functional decomposition of black-box models into explainable predictor effects
por: Köhler, David, et al.
Publicado: (2024)

A novel artificial intelligence‐based classification of highly myopic eyes based on visual function and fundus features
por: Jiaqi Meng, et al.
Publicado: (2025)

A novel artificial intelligence‐based classification of highly myopic eyes based on visual function and fundus features
por: Jiaqi Meng, et al.
Publicado: (2025)

Generative artificial intelligence in dermatology: Recommendations for future studies evaluating the clinical knowledge of models
por: Joshua Pillai, et al.
Publicado: (2024)

Explanation strategies in humans versus current explainable artificial intelligence: Insights from image classification
por: Ruoxi Qi, et al.
Publicado: (2024)

Advancing systemic disease diagnosis through ophthalmic image‐based artificial intelligence
por: Hanpei Miao, et al.
Publicado: (2024)

Deep learning and explainable artificial intelligence for investigating dental professionals' satisfaction with CAD software performance
por: Hang‐Nga Mai, et al.
Publicado: (2024)

Machine learning and explainable artificial intelligence to predict pathologic stage in men with localized prostate cancer
por: Hemal Semwal, et al.
Publicado: (2024)

Copula-enhanced Vision Transformer for high myopia diagnosis through OU UWF fundus images
por: Zhong, Chong, et al.
Publicado: (2025)

Validation of artificial intelligence for epileptic seizure detection: Moving from research into the clinic
por: Jonathan Dan
Publicado: (2024)

Opening the AI black box: program synthesis via mechanistic interpretability
por: Michaud, Eric J., et al.
Publicado: (2024)

$\textit{In vivo}$ fundus imaging and computational refocusing with a diffuser-based fundus camera
por: Simmerer, Corey, et al.
Publicado: (2024)

Adversarial attacks and defenses in explainable artificial intelligence: A survey
por: Baniecki, Hubert, et al.
Publicado: (2023)

Basic principles of artificial intelligence in dermatology explained using melanoma
por: Tim Hartmann, et al.
Publicado: (2024)

Ultrasound placental image texture analysis using artificial intelligence and deep learning models to predict hypertension in pregnancy
por: Urvashi Arora, et al.
Publicado: (2025)

Performance of artificial intelligence chatbots in interpreting clinical images of pressure injuries
por: Makoto Shiraishi, et al.
Publicado: (2024)

Reflections on the use of artificial intelligence in psychiatric diagnosis
por: Marcos F. Rosetti
Publicado: (2023)

Unveiling the power of artificial intelligence for image‐based diagnosis and treatment in endodontics: An ally or adversary?
por: Rocharles Cavalcante Fontenele, et al.
Publicado: (2024)