Radiomics in medical imaging: pitfalls and challenges in clinical management

R Fusco, V Granata, G Grazzini, S Pradella… - Japanese journal of …, 2022 - Springer
Background Radiomics and radiogenomics are two words that recur often in language of
radiologists, nuclear doctors and medical physicists especially in oncology field. Radiomics …

[HTML][HTML] Radiomics in lung diseases imaging: state-of-the-art for clinicians

AN Frix, F Cousin, T Refaee, F Bottari… - Journal of Personalized …, 2021 - mdpi.com
Artificial intelligence (AI) has increasingly been serving the field of radiology over the last 50
years. As modern medicine is evolving towards precision medicine, offering personalized …

[HTML][HTML] A deep learning system to screen novel coronavirus disease 2019 pneumonia

X Xu, X Jiang, C Ma, P Du, X Li, S Lv, L Yu, Q Ni… - Engineering, 2020 - Elsevier
The real-time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral
RNA from sputum or nasopharyngeal swab had a relatively low positive rate in the early …

Coronavirus (covid-19) classification using ct images by machine learning methods

M Barstugan, U Ozkaya, S Ozturk - arxiv preprint arxiv:2003.09424, 2020 - arxiv.org
This study presents early phase detection of Coronavirus (COVID-19), which is named by
World Health Organization (WHO), by machine learning methods. The detection process …

Dual-sampling attention network for diagnosis of COVID-19 from community acquired pneumonia

X Ouyang, J Huo, L **a, F Shan, J Liu… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
The coronavirus disease (COVID-19) is rapidly spreading all over the world, and has
infected more than 1,436,000 people in more than 200 countries and territories as of April 9 …

An efficient deep learning approach to pneumonia classification in healthcare

O Stephen, M Sain, UJ Maduh… - Journal of healthcare …, 2019 - Wiley Online Library
This study proposes a convolutional neural network model trained from scratch to classify
and detect the presence of pneumonia from a collection of chest X‐ray image samples …

A transfer learning method with deep residual network for pediatric pneumonia diagnosis

G Liang, L Zheng - Computer methods and programs in biomedicine, 2020 - Elsevier
Abstract Background and Objective Computer aided diagnosis systems based on deep
learning and medical imaging is increasingly becoming research hotspots. At the moment …

Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning

P Rajpurkar, J Irvin, K Zhu, B Yang, H Mehta… - arxiv preprint arxiv …, 2017 - arxiv.org
We develop an algorithm that can detect pneumonia from chest X-rays at a level exceeding
practicing radiologists. Our algorithm, CheXNet, is a 121-layer convolutional neural network …

Learning to diagnose from scratch by exploiting dependencies among labels

L Yao, E Poblenz, D Dagunts, B Covington… - arxiv preprint arxiv …, 2017 - arxiv.org
The field of medical diagnostics contains a wealth of challenges which closely resemble
classical machine learning problems; practical constraints, however, complicate the …

Coronavirus (COVID-19) classification using deep features fusion and ranking technique

U Özkaya, Ş Öztürk, M Barstugan - Big Data Analytics and Artificial …, 2020 - Springer
COVID-19, which appeared towards the end of 2019, has become a huge threat to public
health. The solution to this threat, which is defined as a global epidemic by the World Health …