Results 181 to 190 of about 42,977 (292)

Machine learning models based on magnetic resonance imaging for predicting Lymphovascular Invasion in Invasive Breast Cancer. [PDF]

PLoS One
Li H, Huang J, Hou J, Chen X, Zhi C, Li Z.   +5 more
europepmc   +1 more source

Development of a Prediction Model for Progression Risk in High‐Grade Gliomas Based on Habitat Radiomics and Pathomics

Annals of Clinical and Translational Neurology, Volume 13, Issue 6, Page 1141-1153, June 2026.
ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Gefei Jiang, Lei Qiu, Kexin Shi, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou   +14 more
wiley   +1 more source

Discriminative and predictive power of radiomics features from preoperative MRI studies in patients with supraspinatus lesions. [PDF]

BMC Musculoskelet Disord
Longo UG, Giaccone P, Bacco L, D'Antoni F, Lalli A, Bandini B, di Naro C, Casciaro C, Nazarian A, Merone M, Schena E, Papalia R.   +11 more
europepmc   +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, Volume 13, Issue 32, 9 June 2026.
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

Machine Learning Radiomics for Predicting Response to MR-Guided Radiotherapy in Unresectable Hepatocellular Carcinoma: A Multicenter Cohort Study

Ke Su,1– 3,* Xin Liu,1,4,* Yue-Can Zeng,5,* Junnv Xu,6,* Han Li,2 Heran Wang,7 Shanshan Du,1 Huadong Wang,1 Jinbo Yue,8 Yong Yin,1 Zhenjiang Li1 1Department of Radiation Physics, Shandong Cancer Hospital and Institute ...
Liu X, Yin Y, Zeng YC, Li H, Li Z, Du S, Su K, Wang H, Xu J, Yue J   +9 more
core  

The Quest for Generalizability in Radiomics

Radiology: Artificial Intelligence, 2020
openaire   +3 more sources

Artificial Intelligence for Bone: Theory, Methods, and Applications

Advanced Intelligent Discovery, Volume 2, Issue 3, June 2026.
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan, Haicang Zhang, Liping Tong, Di Chen   +3 more
wiley   +1 more source

Radiomics analysis of energy CT-derived iodine density maps for predicting lymph node metastasis in colorectal cancer. [PDF]

Quant Imaging Med Surg
Jia Z, Wang D, Pan A, Tang L, Liang Z, Liu X, Wu Y, Qu X, Chen W, Liu X.   +9 more
europepmc   +1 more source

Magnetic Resonance Imaging Radiomics-Based Model for Prediction of Lymph Node Metastasis in Cervical Cancer

Zhenjie Shi, Longlong Lu Medical Imaging Center, Xi’an People’s Hospital (Xi’an Fourth Hospital), Xi’an, Shaanxi Province, People’s Republic of ChinaCorrespondence: Longlong Lu, Medical Imaging Center, Xi’an People’s Hospital (Xi’an Fourth Hospital ...
Lu L, Shi Z
core  

Integrating antibody–drug conjugates into solid tumor oncology: Current standards and future directions

Cancer, Volume 132, Issue S1, 1 June 2026.
Abstract Antibody–drug conjugates (ADCs) represent a major advance in precision oncology, combining the selectivity of monoclonal antibodies with the cytotoxic potency of chemotherapy. By enabling targeted intracellular delivery of highly potent payloads, ADCs aim to maximize antitumor activity while minimizing systemic toxicity. This review summarizes
André Mansinho, Joana Albuquerque, Andreia Lopes, Emiliano Calvo   +3 more
wiley   +1 more source