[HTML][HTML] Criteria for the translation of radiomics into clinically useful tests
EP Huang, JPB O'Connor, LM McShane… - Nature reviews Clinical …, 2023 - nature.com
Computer-extracted tumour characteristics have been incorporated into medical imaging
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …
Radiomics and radiogenomics of ovarian cancer: implications for treatment monitoring and clinical management
C Panico, G Avesani, K Zormpas-Petridis… - Radiologic …, 2023 - radiologic.theclinics.com
Ovarian cancer (OC) is the sixth most common cancer and the fifth cause of cancer-related
death among women. 1 Many pieces of evidence support that high-grade serous OC …
death among women. 1 Many pieces of evidence support that high-grade serous OC …
[HTML][HTML] Combining the transformer and convolution for effective brain tumor classification using MRI images
In the world, brain tumor (BT) is considered the major cause of death related to cancer,
which requires early and accurate detection for patient survival. In the early detection of BT …
which requires early and accurate detection for patient survival. In the early detection of BT …
Gated deep reinforcement learning with red deer optimization for medical image classification
N Ganesh, S Jayalakshmi, RC Narayanan… - IEEE …, 2023 - ieeexplore.ieee.org
One of the most complex areas of image processing is image classification, which is heavily
relied upon in clinical care and educational activities. However, conventional models have …
relied upon in clinical care and educational activities. However, conventional models have …
[HTML][HTML] Head and neck cancer treatment outcome prediction: A comparison between machine learning with conventional radiomics features and deep learning …
Background Radiomics can provide in-depth characterization of cancers for treatment
outcome prediction. Conventional radiomics rely on extraction of image features within a pre …
outcome prediction. Conventional radiomics rely on extraction of image features within a pre …
Bringing machine learning systems into clinical practice: a design science approach to explainable machine learning-based clinical decision support systems
Clinical decision support systems (CDSSs) based on machine learning (ML) hold great
promise for improving medical care. Technically, such CDSSs are already feasible but …
promise for improving medical care. Technically, such CDSSs are already feasible but …
[HTML][HTML] Phenotyping the histopathological subtypes of non-small-cell lung carcinoma: how beneficial is radiomics?
The aim of this study was to investigate the usefulness of radiomics in the absence of well-
defined standard guidelines. Specifically, we extracted radiomics features from multicenter …
defined standard guidelines. Specifically, we extracted radiomics features from multicenter …
[HTML][HTML] A pathomic approach for tumor-infiltrating lymphocytes classification on breast cancer digital pathology images
Background and objectives The detection of tumor-infiltrating lymphocytes (TILs) could aid in
the development of objective measures of the infiltration grade and can support decision …
the development of objective measures of the infiltration grade and can support decision …
[HTML][HTML] Automated Breast Ultrasound (ABUS)-based radiomics nomogram: an individualized tool for predicting axillary lymph node tumor burden in patients with early …
Y Chen, Y Xie, B Li, H Shao, Z Na, Q Wang, H Jing - BMC cancer, 2023 - Springer
Objectives Preoperative evaluation of axillary lymph node (ALN) status is an essential part of
deciding the appropriate treatment. According to ACOSOG Z0011 trials, the new goal of the …
deciding the appropriate treatment. According to ACOSOG Z0011 trials, the new goal of the …
[HTML][HTML] Cluster analysis of autoencoder-extracted FDG PET/CT features identifies multiple myeloma patients with poor prognosis
F-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG
PET/CT) is a robust imaging modality used for staging multiple myeloma (MM) and …
PET/CT) is a robust imaging modality used for staging multiple myeloma (MM) and …