Results 71 to 80 of about 42,977 (292)

PancDS in Real‐World Practice: A Prospective Multicenter Validation of a Clinical Decision‐Support System Bridging Experience Gaps in Pancreatic Lesion Diagnosis

Advanced Science, EarlyView.
A biomimetic artificial intelligence system, PancDS, has been developed to distinguish pancreatic ductal adenocarcinoma from mass‐forming pancreatitis by adaptively integrating clinical data, radiomics, and deep learning features. Validated across multicenter, reader‐study, and prospective settings, PancDS improves diagnostic accuracy, particularly for
Zhibo Wang, Weinuo Qu, Wenwen Cai, Chuhuai Wang, Chenxi Lyu, Qingguo Xie, Qian Chu, Yaqi Shen, Peng Xiao, Feng Li, Qingpeng Zhang, Jiali Li, Jeong Min Lee, Zhen Li   +13 more
wiley   +1 more source

Radiomics analysis of contrast-enhanced computed tomography in predicting the International Neuroblastoma Pathology Classification in neuroblastoma

Insights into Imaging, 2023
Purpose To predict the International Neuroblastoma Pathology Classification (INPC) in neuroblastoma using a computed tomography (CT)-based radiomics approach.
Haoru Wang, Mingye Xie, Xin Chen, Jin Zhu, Li Zhang, Hao Ding, Zhengxia Pan, Ling He   +7 more
doaj   +1 more source

Noninvasive Characterization of Tumor Heterogeneity in HNSCC: From Clinical Utility to Biological Correlates

Advanced Science, EarlyView.
This study establishes a CT‐based radiomics framework to quantify intratumoral heterogeneity (ITH) in HNSCC. Using unsupervised clustering, tumor ROIs and VOIs are analyzed to calculate 2D/3D ITH scores. The score shows strong predictive value for prognosis and immunotherapy response, and is associated with tumor metabolism and immune microenvironment,
Xinwei Chen, Rui Liu, Yuan Zhou, Yin Xiao, Chengmin Feng, Lin Chen, Yanshi Li, Mengna Wang, Zhaobo Cheng, Yuxi Luo, Long Liu, Lijing Niu, Yue Xiang, Juan Peng, Guohua Hu, Min Pan   +15 more
wiley   +1 more source

Radiogenomic correlation of hypoxia-related biomarkers in clear cell renal cell carcinoma

Journal of Cancer Research and Clinical Oncology
Purpose This study aimed to evaluate radiomic models’ ability to predict hypoxia-related biomarker expression in clear cell renal cell carcinoma (ccRCC).
Yijun Shao, Harmony S. Cen, Anu Dhananjay, S. J. Pawan, Xiaomeng Lei, Inderbir S. Gill, Anishka D’souza, Vinay A. Duddalwar   +7 more
doaj   +1 more source

A CT-based deep learning-driven tool for automatic liver tumor detection and delineation in patients with cancer

Cell Reports Medicine
Summary: Liver tumors, whether primary or metastatic, significantly impact the outcomes of patients with cancer. Accurate identification and quantification are crucial for effective patient management, including precise diagnosis, prognosis, and therapy ...
Maria Balaguer-Montero, Adrià Marcos Morales, Marta Ligero, Christina Zatse, David Leiva, Luz M. Atlagich, Nikolaos Staikoglou, Cristina Viaplana, Camilo Monreal, Joaquin Mateo, Jorge Hernando, Alejandro García-Álvarez, Francesc Salvà, Jaume Capdevila, Elena Elez, Rodrigo Dienstmann, Elena Garralda, Raquel Perez-Lopez   +17 more
doaj   +1 more source

An Approach Based on Mammographic Imaging and Radiomics for Distinguishing Male Benign and Malignant Lesions: A Preliminary Study

Frontiers in Oncology, 2021
PurposeTo develop and validate an imaging-radiomics model for the diagnosis of male benign and malignant breast lesions.MethodsNinety male patients who underwent preoperative mammography from January 2011 to December 2018 were enrolled in this study (63 ...
Yan Huang, Yan Huang, Qin Xiao, Qin Xiao, Yiqun Sun, Yiqun Sun, Zhe Wang, Qin Li, Qin Li, He Wang, He Wang, He Wang, Yajia Gu, Yajia Gu   +13 more
doaj   +1 more source

A Foundation Model Based CT Biomarker for Non‐Invasive Prediction of Response to Neoadjuvant Immunochemotherapy in Non‐Small Cell Lung Cancer

Advanced Science, EarlyView.
This study introduces a foundation model‐based biomarker for risk stratification of pathological response in non‐small cell lung cancer. A Vision Mamba super‐resolution model standardizes heterogeneous CT images. A multi‐task Swin Transformer then fine‐tunes a pre‐trained lung foundation model to jointly optimize tumor segmentation and response ...
Yanglan Xu, Shuchang Zhou, Qin Peng, Xiao Bao, Xiaodan Ye, Ahmet Görkem Er, Tong Tong, Mirabela Rusu, Yajia Gu, Mailin Chen, Jing Gong   +10 more
wiley   +1 more source

A Study on Energy Consumption in AI-Driven Medical Image Segmentation

Journal of Imaging
As artificial intelligence advances in medical image analysis, its environmental impact remains largely overlooked. This study analyzes the energy demands of AI workflows for medical image segmentation using the popular Kidney Tumor Segmentation-2019 ...
R. Prajwal, S. J. Pawan, Shahin Nazarian, Nicholas Heller, Christopher J. Weight, Vinay Duddalwar, C.-C. Jay Kuo   +6 more
doaj   +1 more source

Development and optimisation of a preclinical cone beam computed tomography-based radiomics workflow for radiation oncology research

Physics and Imaging in Radiation Oncology, 2023
Background and purpose: Radiomics features derived from medical images have the potential to act as imaging biomarkers to improve diagnosis and predict treatment response in oncology.
Kathryn H. Brown, Neree Payan, Sarah Osman, Mihaela Ghita, Gerard M. Walls, Ileana Silvestre Patallo, Giuseppe Schettino, Kevin M. Prise, Conor K. McGarry, Karl T. Butterworth   +9 more
doaj   +1 more source

Deep Radiomics Features of Median Nerves for Automated Diagnosis of Carpal Tunnel Syndrome With Ultrasound Images

, 2023
Objectives: Ultrasound is widely used in diagnosing carpal tunnel syndrome (CTS). However, the limitations of ultrasound in CTS detection are the lack of objective measures in the detection of nerve abnormality and the operator-dependent nature of ...
Afshin Mohammadi, U. Rajendra Acharya, Ali Abbasian Ardakani, Mohammad Mirza‐Aghazadeh‐Attari, Mirza-Aghazadeh-Attari, Mohammad, Torres-Cuenca, Thomas, Faeghi, Fariborz, Acharya, U. Rajendra, Thomas Torres‐Cuenca, Fariborz Faeghi, Ardakani, Ali Abbasian, Mohammadi, Afshin   +11 more
core   +1 more source