A systematic review and meta‐analysis of predictive and prognostic models for outcome prediction using positron emission tomography radiomics in head and neck …

MM Philip, A Welch, F McKiddie, M Nath - Cancer Medicine, 2023 - Wiley Online Library
Background Positron emission tomography (PET) images of head and neck squamous cell
carcinoma (HNSCC) patients can assess the functional and biochemical processes at …

Performance of radiomics-based artificial intelligence systems in the diagnosis and prediction of treatment response and survival in esophageal cancer: a systematic …

N Menon, N Guidozzi, S Chidambaram… - Diseases of the …, 2023 - academic.oup.com
Radiomics can interpret radiological images with more detail and in less time compared to
the human eye. Some challenges in managing esophageal cancer can be addressed by …

The applications of artificial intelligence in digestive system neoplasms: a review

S Zhang, W Mu, D Dong, J Wei, M Fang, L Shao… - Health Data …, 2023 - spj.science.org
Importance Digestive system neoplasms (DSNs) are the leading cause of cancer-related
mortality with a 5-year survival rate of less than 20%. Subjective evaluation of medical …

Radiomics in oncological PET imaging: a systematic review—Part 2, Infradiaphragmatic cancers, Blood Malignancies, Melanoma and Musculoskeletal Cancers

D Morland, EKA Triumbari, L Boldrini, R Gatta… - Diagnostics, 2022 - mdpi.com
The objective of this review was to summarize published radiomics studies dealing with
infradiaphragmatic cancers, blood malignancies, melanoma, and musculoskeletal cancers …

Radiomic assessment of oesophageal adenocarcinoma: a critical review of 18F-FDG PET/CT, PET/MRI and CT

RJ O'Shea, C Rookyard, S Withey, GJR Cook… - Insights into …, 2022 - Springer
Objectives Radiomic models present an avenue to improve oesophageal adenocarcinoma
assessment through quantitative medical image analysis. However, model selection is …

Esophageal cancer detection framework based on time series information from smear images

C Zhang, D Jia, Z Li, N Wu, Z He, H Jiang… - Expert Systems with …, 2024 - Elsevier
The gold standard for esophageal cancer diagnosis and treatment is the Thinprep Cytologic
Test (TCT) of suspected sections. TCT refers to analyze the features of the lesion areas …

[Retracted] Atom Search Optimization with the Deep Transfer Learning‐Driven Esophageal Cancer Classification Model

NR Alharbe, RM Munshi, MM Khayyat… - Computational …, 2022 - Wiley Online Library
Esophageal cancer (EC) is a commonly occurring malignant tumor that significantly affects
human health. Earlier recognition and classification of EC or premalignant lesions can result …

Evaluation of survival of the patients with metastatic rectal cancer by staging 18F-FDG PET/CT radiomic and volumetric parameters

N Agüloğlu, A Aksu - Revista Española de Medicina Nuclear e Imagen …, 2023 - Elsevier
Objective The aim of this study is to predict the prognosis in patients with metastatic rectal
cancer (mRC) by obtaining a model with machine learning (ML) algorithms through …

Intra and peritumoral PET radiomics analysis to predict the pathological response in breast cancer patients receiving neoadjuvant chemotherapy

A Aksu, ZG Güç, KA Küçüker, A Alacacıoğlu… - Revista Española de …, 2024 - Elsevier
Objective The aim of our study was to evaluate the contribution of 18Fluorine-
Fluorodeoxyglucose Positron Emission Tomography (18F-FDG PET) radiomic data obtained …

Análisis radiómico PET intra y peritumoral para predecir la respuesta patológica en pacientes con cáncer de mama que reciben quimioterapia neoadyuvante

A Aksu, ZG Güç, KA Küçüker, A Alacacıoğlu… - Revista Española de …, 2024 - Elsevier
Objetivo El objetivo de nuestro estudio fue evaluar la contribución de los datos radiómicos
de la tomografía por emisión de positrones con 18 Fluor-fluorodesoxiglucosa (PET con 18 F …