[HTML][HTML] [18F] FDG-PET/CT radiomics and artificial intelligence in lung cancer: technical aspects and potential clinical applications
R Manafi-Farid, E Askari, I Shiri, C Pirich… - Seminars in nuclear …, 2022 - Elsevier
Lung cancer is the second most common cancer and the leading cause of cancer-related
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …
death worldwide. Molecular imaging using [18 F] fluorodeoxyglucose Positron Emission …
Machine learning, deep learning, and mathematical models to analyze forecasting and epidemiology of COVID-19: a systematic literature review
COVID-19 is a disease caused by SARS-CoV-2 and has been declared a worldwide
pandemic by the World Health Organization due to its rapid spread. Since the first case was …
pandemic by the World Health Organization due to its rapid spread. Since the first case was …
[HTML][HTML] Non-contrast Cine Cardiac Magnetic Resonance image radiomics features and machine learning algorithms for myocardial infarction detection
E Avard, I Shiri, G Hajianfar, H Abdollahi… - Computers in Biology …, 2022 - Elsevier
Objective Robust differentiation between infarcted and normal tissue is important for clinical
diagnosis and precision medicine. The aim of this work is to investigate the radiomic …
diagnosis and precision medicine. The aim of this work is to investigate the radiomic …
Two-step machine learning to diagnose and predict involvement of lungs in COVID-19 and pneumonia using CT radiomics
Objective To develop a two-step machine learning (ML) based model to diagnose and
predict involvement of lungs in COVID-19 and non COVID-19 pneumonia patients using CT …
predict involvement of lungs in COVID-19 and non COVID-19 pneumonia patients using CT …
High-dimensional multinomial multiclass severity scoring of COVID-19 pneumonia using CT radiomics features and machine learning algorithms
We aimed to construct a prediction model based on computed tomography (CT) radiomics
features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A …
features to classify COVID-19 patients into severe-, moderate-, mild-, and non-pneumonic. A …
[HTML][HTML] Combating Covid-19 using machine learning and deep learning: Applications, challenges, and future perspectives
COVID-19, a worldwide pandemic that has affected many people and thousands of
individuals have died due to COVID-19, during the last two years. Due to the benefits of …
individuals have died due to COVID-19, during the last two years. Due to the benefits of …
Explainable machine-learning models for COVID-19 prognosis prediction using clinical, laboratory and radiomic features
The SARS-CoV-2 virus pandemic had devastating effects on various aspects of life: clinical
cases, ranging from mild to severe, can lead to lung failure and to death. Due to the high …
cases, ranging from mild to severe, can lead to lung failure and to death. Due to the high …
Self-reporting with checklists in artificial intelligence research on medical imaging: a systematic review based on citations of CLAIM
B Kocak, A Keles, T Akinci D'Antonoli - European Radiology, 2024 - Springer
Objective To evaluate the usage of a well-known and widely adopted checklist, Checklist for
Artificial Intelligence in Medical imaging (CLAIM), for self-reporting through a systematic …
Artificial Intelligence in Medical imaging (CLAIM), for self-reporting through a systematic …
Self-reported checklists and quality scoring tools in radiomics: a meta-research
B Kocak, T Akinci D'Antonoli, E Ates Kus, A Keles… - European …, 2024 - Springer
Objective To evaluate the use of reporting checklists and quality scoring tools for self-
reporting purposes in radiomics literature. Methods Literature search was conducted in …
reporting purposes in radiomics literature. Methods Literature search was conducted in …
Chest X-ray Images for Lung Disease Detection Using Deep Learning Techniques: A Comprehensive Survey
MAA Al-qaness, J Zhu, D AL-Alimi, A Dahou… - … Methods in Engineering, 2024 - Springer
In medical imaging, the last decade has witnessed a remarkable increase in the availability
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …
and diversity of chest X-ray (CXR) datasets. Concurrently, there has been a significant …