Results 61 to 70 of about 52,953 (291)

Three-Dimensional Radiomics Features From Multi-Parameter MRI Combined With Clinical Characteristics Predict Postoperative Cerebral Edema Exacerbation in Patients With Meningioma

Frontiers in Oncology, 2021
BackgroundPostoperative cerebral edema is common in patients with meningioma. It is of great clinical significance to predict the postoperative cerebral edema exacerbation (CEE) for the development of individual treatment programs in patients with ...
Bing Xiao, Yanghua Fan, Zhe Zhang, Zilong Tan, Huan Yang, Wei Tu, Lei Wu, Xiaoli Shen, Hua Guo, Zhen Wu, Xingen Zhu   +10 more
doaj   +1 more source

Tensor Radiomics: Paradigm for Systematic Incorporation of Multi-Flavoured Radiomics Features

Quantitative Imaging in Medicine and Surgery, 2022
Background and Objectives: Radiomics features extract quantitative information from medical images, towards the derivation of biomarkers for clinical tasks, such as diagnosis, prognosis, or treatment response assessment. Different image discretization parameters (e.g.
Arman Rahmim, Amirhosein Toosi, Mohammad R. Salmanpour, Natalia Dubljevic, Ian Janzen, Isaac Shiri, Mohamad A. Ramezani, Ren Yuan, Cheryl Ho, Habib Zaidi, Calum MacAulay, Carlos Uribe, Fereshteh Yousefirizi   +12 more
openaire   +4 more sources

Artificial Intelligence in Systemic Sclerosis: Clinical Applications, Challenges, and Future Directions

Arthritis Care &Research, EarlyView.
Systemic sclerosis (SSc) is a rare autoimmune disease defined by immune dysregulation, vasculopathy, and progressive fibrosis of the skin and internal organs. Despite advances in care, major complications such as interstitial lung disease (ILD) and myocardial involvement remain the leading causes of morbidity and mortality.
Cristiana Sieiro Santos, José Miguel Sequí‐Sabater, Diego Benavent   +2 more
wiley   +1 more source

Prediction of PD-L1 and CD68 in Clear Cell Renal Cell Carcinoma with Green Learning

Journal of Imaging
Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cancer. Extensive efforts have been made to utilize radiomics from computed tomography (CT) imaging to predict tumor immune microenvironment (TIME) measurements. This study proposes
Yixing Wu, Alexander Shieh, Steven Cen, Darryl Hwang, Xiaomeng Lei, S. J. Pawan, Manju Aron, Inderbir Gill, William D. Wallace, C.-C. Jay Kuo, Vinay Duddalwar   +10 more
doaj   +1 more source

Development of a MRI-Based Radiomics Nomogram for Prediction of Response of Patients With Muscle-Invasive Bladder Cancer to Neoadjuvant Chemotherapy

Frontiers in Oncology, 2022
ObjectiveTo develop and evaluate the performance of a magnetic resonance imaging (MRI)-based radiomics nomogram for prediction of response of patients with muscle-invasive bladder cancer (MIBC) to neoadjuvant chemotherapy (NAC).MethodsA total of 70 ...
Xinxin Zhang, Yichen Wang, Jin Zhang, Lianyu Zhang, Sicong Wang, Yan Chen   +5 more
doaj   +1 more source

Radiomics-Guided Deep Learning Networks Classify Differential Diagnosis of Parkinsonism. [PDF]

The differential diagnosis between atypical Parkinsonian syndromes may be challenging and critical. We aimed to proposed a radiomics-guided deep learning (DL) model to discover interpretable DL features and further verify the proposed model through the ...
Wang, Luyao, Lu, Jiaying, Shi, Kuangyu, Shaoyou Wu, Ronghua Ling, Ping Wu, Jiang, Jiehui, Yan, Zhuangzhi, Liu, Yingqian, Min Wang, Yingqian Liu, Jiaying Lu, Juanjuan Jiang, Zuo, Chuantao, Ling, Ronghua, Wu, Shaoyou, Luyao Wang, Chuantao Zuo, Zhuangzhi Yan, Ge, Jingjie, Jiehui Jiang, Jingjie Ge, Wu, Ping, Jiang, Juanjuan, Wang, Min, Kuangyu Shi   +25 more
core   +2 more sources

Beyond Visual Scoring: Computational Computed Tomography Analysis for High‐Resolution Computed Tomography–Based Quantification of Interstitial Lung Disease in Inflammatory Rheumatic Disease

Arthritis Care &Research, EarlyView.
Interstitial lung disease (ILD) is a significant cause of morbidity and mortality in patients with inflammatory rheumatic disorders (IRDs). High‐resolution computed tomography (HRCT) is widely considered the gold standard for the noninvasive assessment of ILD; however, its interpretation is constrained by substantial interobserver variability and the ...
Alexander Pfeil, Tobias Hoffmann, Ulf Teichgräber, Diane Renz, Denise Beckmann, Gunter Wolf, Nicole Schadewaldt, Bianca Lassen‐Schmidt   +7 more
wiley   +1 more source

Towards a Compositional Framework for Describing Human Phenotypes

Advanced Science, EarlyView.
The Phenotype Assembly Method (PhenoAM) decomposes phenotype variables into measurable Features and typed Qualifiers, enabling standardized, machine‐readable Phenome Data Elements (PhenoDEs) that preserve measurement context. Applied in the International Human Phenome Project (IHPP), the framework yields 58 371 PhenoDEs and supports component‐level ...
Wanting Hu, Yunchao Ling, Xinyue Hu, Wei Chen, Rong Zhou, Xinhao Zhuang, Yanfeng Jiang, Jialu Zhao, Xingdong Chen, Jingchun Luo, Li Jin, Guoqing Zhang   +11 more
wiley   +1 more source

Machine Learning Model Integrating CT Radiomics of the Lung to Predict Checkpoint Inhibitor Pneumonitis in Patients with Advanced Cancer

Technology in Cancer Research & Treatment
Objective Checkpoint inhibitor pneumonitis (CIP) is a potentially life-threatening immune-related adverse event. Efficient strategies to select patients at risk are still required.
François Cousin MD, PhD, Thomas Louis MS, PhD, Pierre Frères MD, PhD, Julien Guiot MD, PhD, Mariaelena Occhipinti MD, Fabio Bottari MS, Wim Vos MS, Roland Hustinx MD, PhD   +7 more
doaj   +1 more source

DeepLNM: A Multimodal Model for Predicting Lymph Node Metastasis in Colorectal Cancer

Advanced Science, EarlyView.
Traditional diagnosis may miss positive LNM cases, and pathologists face a workload; therefore, we develop DeepLNM, a multimodal model that predicts lymph node metastasis in colorectal cancer from H&E WSIs, CT images, and text. DeepLNM is robust across internal, external, and prospective cohorts and, in a user study, improves diagnostic accuracy while ...
Zhengyu Zhang, Chengyu Lu, Zhen Wang, Zhijian Cen, Yangshu Zhou, Danyi Li, Qi Xie, Bingbing Li, Shujing Guo, Zhijun Gan, Er‐ran Zhu, Jinbang Li, Aihetaimu Aimaier, Rui Mao, Weihao Qiu, Chenglong Zhao, Ying Tan, Xiaolin Liu, Huiting Ma, Tiansu Geng, Peiyue Wu, Huijun Du, Yu Wang, Yueping Liu, Li Liang   +24 more
wiley   +1 more source