Results 61 to 70 of about 55,768 (244)

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

Radiomics signature of computed tomography imaging for prediction of survival and chemotherapeutic benefits in gastric cancerResearch in context

EBioMedicine, 2018
To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and chemotherapeutic benefits. In this multicenter retrospective analysis, we analyzed the radiomics features of portal venous-phase computed tomography in ...
Yuming Jiang, Chuanli Chen, Jingjing Xie, Wei Wang, Xuefan Zha, Wenbing Lv, Hao Chen, Yanfeng Hu, Tuanjie Li, Jiang Yu, Zhiwei Zhou, Yikai Xu, Guoxin Li   +12 more
doaj   +1 more source

Combination Immunotherapy as a Promising Strategy to Overcome Immunotherapy Resistance: From Emergence to Next‐Generation Approaches

Advanced Science, EarlyView.
This review examines emerging combination immunotherapy strategies tailored to distinct tumor microenvironments and highlights next‐generation biomarkers that guide response prediction and treatment personalization. It integrates lessons from unsuccessful trials, addresses toxicity challenges, and outlines approaches for early biomarker discovery and ...
Asmita Pandey, Sudhir Kumar Rai, Li Ma, Lauren Higa, Vedbar Khadka, Hua Yang, Youping Deng   +6 more
wiley   +1 more source

Radiomics: a critical step towards integrated healthcare [PDF]

Insights into Imaging, 2018
Medical imaging is a vital part of the clinical decision-making process, especially in an oncological setting. Radiology has experienced a great wave of change, and the advent of quantitative imaging has provided a unique opportunity to analyse patient images objectively.
Bodalal, Zuhir, Trebeschi, Stefano, Beets-Tan, Regina   +2 more
openaire   +4 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 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

Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction

, 2018
Deep learning for regression tasks on medical imaging data has shown promising results. However, compared to other approaches, their power is strongly linked to the dataset size.
A Jungo, AW Awad, B Fischl, BH Menze, CH Lampert, DN Louis, DR Cox, G Wang, J Lao, JJ Griethuysen van, Julián Pérez-Beteta, N Sanai, R Meier, R Tibshirani, RJ Gillies, S Bakas, S Pereira, S Rathore, Spyridon Bakas, Spyridon Bakas, T Hastie, TC Steed, Y Li   +22 more
core   +1 more source

Integrating Radiomics and Computational Pathology to Predict Early Recurrence of Pancreatic Ductal Adenocarcinoma and Uncover Its Biological Basis in Tumor Microenvironment

Advanced Science, EarlyView.
Accurate prediction of early recurrence in pancreatic ductal adenocarcinoma is vital for optimizing treatment. A novel, integrated radiomics‐pathology machine learning model successfully forecasts recurrence risks by analyzing preoperative CT images and computational pathology.
Sihang Cheng, Fuze Cong, Shenbo Zhang, Rui Lv, Wenjia Zhang, Xinyi Ke, Juncheng Wu, Zhonghe Zhao, Kui Zhao, Di Dong, Ruofan Zhang, Zhengyu Jin, Max Seidensticker, Zhiwei Wang, Huanwen Wu, Xianlin Han, Nan Hong, Huadan Xue   +17 more
wiley   +1 more source

Differentiation of retroperitoneal paragangliomas and schwannomas based on computed tomography radiomics

Scientific Reports, 2023
The purpose of this study was to differentiate the retroperitoneal paragangliomas and schwannomas using computed tomography (CT) radiomics. This study included 112 patients from two centers who pathologically confirmed retroperitoneal pheochromocytomas ...
Yuntai Cao, Zhan Wang, Jialiang Ren, Wencun Liu, Huiwen Da, Xiaotong Yang, Haihua Bao   +6 more
doaj   +1 more source

Differential Diagnosis of Type 1 and Type 2 Papillary Renal Cell Carcinoma Based on Enhanced CT Radiomics Nomogram

Frontiers in Oncology, 2022
ObjectivesTo construct a contrast-enhanced CT-based radiomics nomogram that combines clinical factors and a radiomics signature to distinguish papillary renal cell carcinoma (pRCC) type 1 from pRCC type 2 tumours.MethodsA total of 131 patients with 60 in
Yankun Gao, Xingwei Wang, Shihui Wang, Yingying Miao, Chao Zhu, Cuiping Li, Guoquan Huang, Yan Jiang, Jianying Li, Xiaoying Zhao, Xingwang Wu   +10 more
doaj   +1 more source