Machine learning applications for COVID-19 outbreak management
Recently, the COVID-19 epidemic has resulted in millions of deaths and has impacted
practically every area of human life. Several machine learning (ML) approaches are …
practically every area of human life. Several machine learning (ML) approaches are …
[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 …
COVID-19 prognostic modeling using CT radiomic features and machine learning algorithms: Analysis of a multi-institutional dataset of 14,339 patients
Background We aimed to analyze the prognostic power of CT-based radiomics models
using data of 14,339 COVID-19 patients. Methods Whole lung segmentations were …
using data of 14,339 COVID-19 patients. Methods Whole lung segmentations were …
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 …
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 …
[HTML][HTML] Multi-institutional PET/CT image segmentation using federated deep transformer learning
Abstract Background and Objective Generalizable and trustworthy deep learning models for
PET/CT image segmentation necessitates large diverse multi-institutional datasets …
PET/CT image segmentation necessitates large diverse multi-institutional datasets …
Diagnosis of COVID-19 using CT image radiomics features: a comprehensive machine learning study involving 26,307 patients
Purpose To derive and validate an effective radiomics-based model for differentiation of
COVID-19 pneumonia from other lung diseases using a very large cohort of patients …
COVID-19 pneumonia from other lung diseases using a very large cohort of patients …
Deep learning-based non-rigid image registration for high-dose rate brachytherapy in inter-fraction cervical cancer
In this study, an inter-fraction organ deformation simulation framework for the locally
advanced cervical cancer (LACC), which considers the anatomical flexibility, rigidity, and …
advanced cervical cancer (LACC), which considers the anatomical flexibility, rigidity, and …
Fast and accurate U-net model for fetal ultrasound image segmentation
V Ashkani Chenarlogh, M Ghelich Oghli… - Ultrasonic …, 2022 - journals.sagepub.com
U-Net based algorithms, due to their complex computations, include limitations when they
are used in clinical devices. In this paper, we addressed this problem through a novel U-Net …
are used in clinical devices. In this paper, we addressed this problem through a novel U-Net …