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1.
IEEE Trans Neural Netw Learn Syst ; PP2023 Jun 07.
Article in English | MEDLINE | ID: covidwho-20236897

ABSTRACT

Detecting pneumonia, especially coronavirus disease 2019 (COVID-19), from chest X-ray (CXR) images is one of the most effective ways for disease diagnosis and patient triage. The application of deep neural networks (DNNs) for CXR image classification is limited due to the small sample size of the well-curated data. To tackle this problem, this article proposes a distance transformation-based deep forest framework with hybrid-feature fusion (DTDF-HFF) for accurate CXR image classification. In our proposed method, hybrid features of CXR images are extracted in two ways: hand-crafted feature extraction and multigrained scanning. Different types of features are fed into different classifiers in the same layer of the deep forest (DF), and the prediction vector obtained at each layer is transformed to form distance vector based on a self-adaptive scheme. The distance vectors obtained by different classifiers are fused and concatenated with the original features, then input into the corresponding classifier at the next layer. The cascade grows until DTDF-HFF can no longer gain benefits from the new layer. We compare the proposed method with other methods on the public CXR datasets, and the experimental results show that the proposed method can achieve state-of-the art (SOTA) performance. The code will be made publicly available at https://github.com/hongqq/DTDF-HFF.

2.
Journal of Physics: Conference Series ; 1955(1), 2021.
Article in English | ProQuest Central | ID: covidwho-1286530

ABSTRACT

The global pandemic of COVID-19 has brought huge public health challenges to the world. To meet the challenge, researchers worldwide have carried out a series of clinical studies. This article aims to analyze the progress of COVID-19, and explore the development and main research directions in 2020. The clinical trials focus on the design of the trial plan, which can be registered on the platform after the design is completed. The purpose of clinical publications is to publish trial results, focusing on in vitro tests, drug screening and so on. Based on these characteristics, this paper analyzes both clinical publications and clinical trials, and explores the development of global clinical research in 2020 from countries, intervention methods and trial designs. The experimental results show that the United States and China have published the most publications and carried out the most clinical trials. The maximum intervention methods in clinical trials & publications are focused on the drugs.

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