Abstract
Qingying Sun, Feifei Meng, Guangxi Shi, Wenshi Tian, Xulei Wang, Jiazheng Yan
Abstract
Authors
Institutions
No ROR-resolved institution is linked to this work yet.
Provenance
crossref
Confidence 100%
unpaywall
Confidence 95%
datacite
Confidence 0%
No local reference links have been materialized yet.
No local citing links have been materialized yet.
Update from the 2022 World Health Organization Classification of Thyroid Tumors: A Standardized Diagnostic Approach
10.3803/enm.2022.1553 · 2022
Application of Hyperspectral Imaging and Machine Learning for Differential Diagnosis of Hashimoto's Thyroiditis and Papillary Thyroid Carcinoma
2025
Differential Diagnosis of Papillary Thyroid Carcinoma and Nodular Goiter With Papillary Hyperplasia Using Hyperspectral Imaging Technology
10.1002/jbio.202500200 · 2025
Thyroid Carcinoma Detection on Whole Histologic Slides Using Hyperspectral Imaging and Deep Learning
2022
Automatic detection of head and neck squamous cell carcinoma on histologic slides using hyperspectral microscopic imaging
10.1117/1.jbo.27.4.046501 · 2022
Diagnosis of cholangiocarcinoma from microscopic hyperspectral pathological dataset by deep convolution neural networks
10.1016/j.ymeth.2021.04.005 · 2022
Quantitative melanoma diagnosis using spectral phasor analysis of hyperspectral imaging from label-free slices
10.3389/fonc.2023.1296826 · 2023
Identification of gastric cancer types based on hyperspectral imaging technology
10.1002/jbio.202300276 · 2024
Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral Imaging
10.3390/cancers14174292 · 2022
Deep learning for rapid virtual H&E staining of label-free glioma tissue from hyperspectral images
10.1016/j.compbiomed.2024.108958 · 2024
Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications
10.1117/1.jbo.31.3.030901 · 2026
Advancing hyperspectral imaging and machine learning tools toward clinical adoption in tissue diagnostics: A comprehensive review
10.1063/5.0240444 · 2024
Joint Diagnostic Method of Tumor Tissue Based on Hyperspectral Spectral-Spatial Transfer Features
10.3390/diagnostics13122002 · 2023
Accurate classification of glomerular diseases by hyperspectral imaging and transformer
10.1016/j.cmpb.2024.108285 · 2024
Multiple instance learning for digital pathology: A review of the state-of-the-art, limitations & future potential
10.1016/j.compmedimag.2024.102337 · 2024
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
10.1136/bmj-2023-078378 · 2024
The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence
10.1038/s41591-025-03953-8 · 2025
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
10.1136/bmj-2024-082505 · 2025
Toward Explainable Artificial Intelligence for Precision Pathology
10.1146/annurev-pathmechdis-051222-113147 · 2024
Machine learning in computational histopathology: Challenges and opportunities
10.1002/gcc.23177 · 2023
Polarized hyperspectral microscopic imaging system for enhancing the visualization of collagen fibers and head and neck squamous cell carcinoma
10.1117/1.jbo.29.1.016005 · 2024
A semi-supervised segmentation method for microscopic hyperspectral pathological images based on multi-consistency learning
10.3389/fonc.2024.1396887 · 2024
Hybrid brain tumor classification of histopathology hyperspectral images by linear unmixing and an ensemble of deep neural networks
10.1049/htl2.12084 · 2024
Intraoperative Assessment of Tumor Margins in Tissue Sections with Hyperspectral Imaging and Machine Learning
10.3390/cancers15010213 · 2023
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
10.1136/bmj-2024-081554 · 2025
No additional external references are available.