Results 181 to 190 of about 9,876,514 (407)

Classification of Pulmonary Nodules Using Multimodal Feature‐Driven Graph Convolutional Networks with Specificity Proficiency

Advanced Intelligent Systems, EarlyView.
The radiomics feature could save the storage space of all medical samples; on the other hand, it avoids data leakage. Graph convolutional neural networks could summarize the similarity of benign and malignant pulmonary nodules to improve the performance in distinguishing them with radiomics and common clinical features.
Renjie Xu, Zhanlue Liang, Dan Wang, Rui Zhang, Jiayi Li, Lingfeng Bi, Kai Zhang, Weimin Li   +7 more
wiley   +1 more source

A Case of Graves's Disease: its Treatment, first by Medical Methods, and later by Excision of one of the Lobes and the Isthmus of the Thyroid Gland [PDF]

, 1911
C. H. Pring, Arthur John Evans
openalex   +1 more source

Enhancing Spinal Metastasis Detection and Feature Evaluation on Computed Tomography Scans Using Deep‐Learning Systems

Advanced Intelligent Systems, EarlyView.
A deep‐learning system (DLS) is developed for the automatic detection of spinal metastases and the evaluation of associated features using computed tomography imaging. A multireader, multicase analysis and a prospective multicenter cohort study are conducted to evaluate the diagnostic performance.
Zhiyu Wang, Guangyu Yao, Shengyuan Xu, Yifeng Gu, Yujie Chang, Jing Sun, Jingyi Guo, Shiqi Peng, Bolin Lai, Xiaoyun Zhang, Chunbin Wang, Haiying Jiang, Surong Chen, Yanfeng Wang, Ya Zhang, Yuehua Li, Hui Zhao   +16 more
wiley   +1 more source

The Gransmus Wilson Lectures ON THE PATHOLOGY AND DISEASES OF THE THYROID GLAND. [PDF]

, 1901
Walter Edmunds
openalex   +1 more source

R‐APEX: A Knowledge Graph–Based Platform for the Elucidation of the Toxicological Mechanisms of Ambient Particulate Matter

Advanced Intelligent Systems, EarlyView.
R‐APEX is a knowledge graph platform developed to investigate how air pollutants such as particularly fine particulate matter (PM2.5) affect human health. By integrating large‐scale biomedical data and using machine learning, it reveals pollutant–gene–disease associations.
Zhixing Zhu, Jingcheng Yang, Xiaofei Li, Zhijie Zheng, Georgi Z. Genchev, Yuchen Ye, Liang Liu, Zihan Ran   +7 more
wiley   +1 more source

MetaQ: fast, scalable and accurate metacell inference via single-cell quantization

Nature Communications
To overcome the computational barriers of analyzing large-scale single-cell sequencing data, we introduce MetaQ, a metacell algorithm that scales to arbitrarily large datasets with linear runtime and constant memory usage.
Yunfan Li, Hancong Li, Yijie Lin, Dan Zhang, Dezhong Peng, Xiting Liu, Jie Xie, Peng Hu, Lu Chen, Han Luo, Xi Peng   +10 more
doaj   +1 more source

The Grasmus Milson Lectures ON THE PATHOLOGY AND DISEASES OF THE THYROID GLAND. [PDF]

, 1901
Walter Edmunds
openalex   +1 more source

Clinlabomics‐Enabled Blending Ensemble Learning for Low‐Cost Pan‐Cancer Detection and Classification Using Routine Clinical Laboratory Data

Advanced Intelligent Systems, EarlyView.
Researchers develop clinlabomics assisted for cancer identification, an artificial intelligence‐powered system using routine clinical lab data to detect and identify 10 cancer types. Tested on 19 199 individuals, it achieves 90.39% sensitivity and 82.41% specificity in cancer detection, with 72.57% accuracy in identifying specific cancer types ...
Bowen Zhang, Lin Li, Long Cheng, Yujie Liu, Zhaoqing Liu, Jiangpeng Wu, Pengyi Zhang, Jiarui Wang, Dekui Zhang, Shuyan Li   +9 more
wiley   +1 more source

Practical Aspect of Thyroid Disease

, 1949
NULL AUTHOR_ID
openalex   +1 more source

Mycosis Fungoides, Sézary Syndrome, and Cutaneous B‐Cell Lymphomas: 2025 Update on Diagnosis, Risk‐Stratification, and Management

American Journal of Hematology, EarlyView.
ABSTRACT Disease Overview Primary cutaneous lymphomas are a rare and heterogeneous group of extranodal lymphomas that require the integration of clinical and histopathologic data for classification and treatment. Diagnosis Diagnosis and disease classification is based on histopathologic review and immunohistochemical staining of an appropriate skin ...
Alexandra C. Hristov, Trilokraj Tejasvi, Ryan A. Wilcox   +2 more
wiley   +1 more source