[HTML][HTML] Radiomics and artificial intelligence in lung cancer screening
F Binczyk, W Prazuch, P Bozek… - Translational lung cancer …, 2021 - ncbi.nlm.nih.gov
Lung cancer is responsible for more fatalities than any other cancer worldwide, with 1.76
million associated deaths reported in 2018. The key issue in the fight against this disease is …
million associated deaths reported in 2018. The key issue in the fight against this disease is …
Towards clinical application of image mining: a systematic review on artificial intelligence and radiomics
Purpose The aim of this systematic review was to analyse literature on artificial intelligence
(AI) and radiomics, including all medical imaging modalities, for oncological and non …
(AI) and radiomics, including all medical imaging modalities, for oncological and non …
Machine learning in oncology: a clinical appraisal
R Cuocolo, M Caruso, T Perillo, L Ugga, M Petretta - Cancer letters, 2020 - Elsevier
Abstract Machine learning (ML) is a branch of artificial intelligence centered on algorithms
which do not need explicit prior programming to function but automatically learn from …
which do not need explicit prior programming to function but automatically learn from …
On the performance of lung nodule detection, segmentation and classification
Computed tomography (CT) screening is an effective way for early detection of lung cancer
in order to improve the survival rate of such a deadly disease. For more than two decades …
in order to improve the survival rate of such a deadly disease. For more than two decades …
Multimodal radiomic features for the predicting gleason score of prostate cancer
A Chaddad, MJ Kucharczyk, T Niazi - Cancers, 2018 - mdpi.com
Background: Novel radiomic features are enabling the extraction of biological data from
routine sequences of MRI images. This study's purpose was to establish a new model …
routine sequences of MRI images. This study's purpose was to establish a new model …
Deep CNN models for predicting COVID-19 in CT and x-ray images
Purpose: Coronavirus disease 2019 (COVID-19) is a new infection that has spread
worldwide and with no automatic model to reliably detect its presence from images. We aim …
worldwide and with no automatic model to reliably detect its presence from images. We aim …
The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features
Radiomics extracts high-throughput quantitative data from medical images to contribute to
precision medicine. Radiomic shape features have been shown to correlate with patient …
precision medicine. Radiomic shape features have been shown to correlate with patient …
Quantitative imaging decision support (QIDSTM) tool consistency evaluation and radiomic analysis by means of 594 metrics in lung carcinoma on chest CT scan
Objective: To evaluate the consistency of the quantitative imaging decision support
(QIDSTM) tool and radiomic analysis using 594 metrics in lung carcinoma on chest CT scan …
(QIDSTM) tool and radiomic analysis using 594 metrics in lung carcinoma on chest CT scan …
A systematic review and meta-analysis of the prognostic value of radiomics based models in non-small cell lung cancer treated with curative radiotherapy
Background and purpose Radiomics allows extraction of quantifiable features from imaging.
This study performs a systematic review and meta-analysis of the performance of radiomics …
This study performs a systematic review and meta-analysis of the performance of radiomics …
Radiomics in pulmonary lesion imaging
OBJECTIVE. Diagnostic imaging has traditionally relied on a limited set of qualitative
imaging characteristics for the diagnosis and management of lung cancer. Radiomics—the …
imaging characteristics for the diagnosis and management of lung cancer. Radiomics—the …