Results 51 to 60 of about 42,977 (292)

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

open access: yesEJNMMI 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   +8 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

open access: yesFrontiers 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   +5 more
doaj   +1 more source

Comparison of Magnetic Resonance Imaging-Based Radiomics Features with Nomogram for Prediction of Prostate Cancer Invasion

open access: yes, 2023
Yang Liu X-Ray Department, The No.1 People’s Hospital of Huzhou, Huzhou, Zhejiang, 313000, People’s Republic of ChinaCorrespondence: Yang Liu, X-ray department, The No.1 People’s hospital of Huzhou, No.
Liu Y
core  

CT-based radiomics for differentiating renal tumours: a systematic review

open access: yes, 2021
PURPOSE: Differentiating renal tumours into grades and tumour subtype from medical imaging is important for patient management; however, there is an element of subjectivity when performed qualitatively. Quantitative analysis such as radiomics may provide
Bhandari, Abhishta   +5 more
core   +1 more source

A CT-based radiomics approach to predict intra-tumoral tertiary lymphoid structures and recurrence of intrahepatic cholangiocarcinoma

open access: yesInsights into Imaging, 2023
Purpose To predict the tertiary lymphoid structures (TLSs) status and recurrence-free survival (RFS) of intrahepatic cholangiocarcinoma (ICC) patients using preoperative CT radiomics.
Ying Xu   +13 more
doaj   +1 more source

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

open access: yesFrontiers 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   +10 more
doaj   +1 more source

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

open access: yesSSRN Electronic Journal, 2022
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. bin number or size), convolutional filters, segmentation perturbation, or multi-modality fusion levels can be ...
Arman Rahmim   +12 more
openaire   +3 more sources

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

open access: yesAging 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   +4 more
wiley   +1 more source

Radiomics in Spine Surgery

open access: yesInternational Journal of Spine Surgery, 2023
Radiomics is an emerging approach to analyze clinical images with the purpose of revealing quantitative features that are unvisible to the naked eye. Radiomic features can be further combined with clinical data and genomic information to formulate prediction models using machine learning algorithms or manual statistical analysis.
Daniel, Alsoof   +5 more
openaire   +2 more sources

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

open access: yesArthritis 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   +2 more
wiley   +1 more source

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