Results 61 to 70 of about 43,566 (284)

Risk Prediction Models for Recurrence After Curative Treatment of Early‐Stage or Locally Advanced Lung Cancer: A Systematic Review

Aging and Cancer, EarlyView.
This systematic review synthesizes prognostic models for survival and recurrence in resected non‐small cell lung cancer. While many models demonstrate moderate to good discrimination, few are externally validated and reporting quality is variable, limiting clinical applicability and highlighting the need for robust, transparent model development ...
Evangeline Samuel, S. Tissera, E. Paul, J. Zalcberg, R. G. Stirling   +4 more
wiley   +1 more source

Peritumoral Dilation Radiomics of Gadoxetate Disodium-Enhanced MRI Excellently Predicts Early Recurrence of Hepatocellular Carcinoma without Macrovascular Invasion After Hepatectomy [PDF]

, 2021
Huanhuan Chong,1,2 Yuda Gong,3 Xianpan Pan,4 Aie Liu,4 Lei Chen,4 Chun Yang,1 Mengsu Zeng1,2,5 1Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, 200032, People’s Republic of China; 2Shanghai Institute of Medical Imaging ...
Pan X, Chong H, Chen L, Zeng M, Liu A, Gong Y, Yang C   +6 more
core  

Integrated PANoptosis Profiling Identifies Immunosuppressive Subtypes and a Prognostic Signature With Functional Validation of MLKL in Glioblastoma

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective The prognosis of glioblastoma (GBM) remains highly unfavorable, largely due to high tumor heterogeneity and an immunosuppressive microenvironment. However, the functional role of PANoptosis in this context is poorly understood. Methods Patients were stratified via K‐means clustering. A risk score model was constructed using prognosis‐
Langfei Tian, Minghui Zhao, Yuanbo Hu, Kaiyue Wang, Haiguang Liu, Zetong Bai, Kebin Zheng   +6 more
wiley   +1 more source

The role of radiomics in dentistry and oral radiology [PDF]

Technological advances in healthcare sector have led to an increasing use of new digital techniques for diagnosis and therapeutics in medical and dental professions.
Tannishtha ., Shruthi Hegde, Vidya Ajila, G. Subhas Babu, B.S. Shama   +4 more
core   +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

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

Value of 18F-FDG-PET/CT radiomics combined with clinical variables in the differential diagnosis of malignant and benign vertebral compression fractures

EJNMMI Research, 2023
Background Vertebral compression fractures (VCFs) are common clinical problems that arise from various reasons. The differential diagnosis of benign and malignant VCFs is challenging.
Xun Wang, Dandan Zhou, Yu Kong, Nan Cheng, Ming Gao, Guqing Zhang, Junli Ma, Yueqin Chen, Shuang Ge   +8 more
doaj   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Shear-Wave Elastography-Based Radiomics Nomogram for the Prediction of Cardiovascular Disease in Patients with Diabetic Kidney Disease [PDF]

, 2023
Fei Meng, Qin Wu, Wei Zhang, Shirong Hou Department of Ultrasound, Xuan Cheng City Central Hospital, Xuancheng, Anhui, People’s Republic of ChinaCorrespondence: Fei Meng, Xuan Cheng City Central Hospital, No.
Meng F, Zhang W, Wu Q, Hou S
core  

Delta-radiomics Entropy Based on Tumor Heterogeneity Concept – Response Predictor to Irradiation for Unresectable/recurrent Glioblastoma [PDF]

, 2022
Although adjuvant radiotherapy in combination with Temozolomide administration has clearly demonstrated the benefit in improving the prognosis of patients with multiforme glioblastoma, radiotherapy as only treatment or in combination with systemic ...
Camil Ciprian MIRESTEAN, Roxana Irina IANCU, Dragos Teodor IANCU   +2 more
core   +1 more source