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In a worldwide health crisis as exigent as COVID-19, there has become a pressing need for rapid, reliable diagnostics. Currently, popular testing methods such as reverse transcription polymerase chain reaction (RT-PCR) can have high false…

COVID-19 pandemic continues to spread rapidly over the world and causes a tremendous crisis in global human health and the economy. Its early detection and diagnosis are crucial for controlling the further spread. Many deep learning-based…

A crucial step within secondary analysis of electronic health records (EHRs) is to identify the patient cohort under investigation. While EHRs contain medical billing codes that aim to represent the conditions and treatments patients may…

With a Coronavirus disease (COVID-19) case count exceeding 10 million worldwide, there is an increased need for a diagnostic capability. The main variables in increasing diagnostic capability are reduced cost, turnaround or diagnosis time,…

This work presents an outer product-based approach to fuse the embedded representations generated from the spectrograms of cough, breath, and speech samples for the automatic detection of COVID-19. To extract deep learnt representations…

This study presents a comprehensive review of the potential of multimodal deep learning (DL) in medical diagnosis, using COVID-19 as a case example. Motivated by the success of artificial intelligence applications during the COVID-19…

The Coronavirus (COVID-19), which is an infectious pulmonary disorder, has affected millions of people and has been declared as a global pandemic by the WHO. Due to highly contagious nature of COVID-19 and its high possibility of causing…

Propose: Troubling countries one after another, the COVID-19 pandemic has dramatically affected the health and well-being of the world's population. The disease may continue to persist more extensively due to the increasing number of new…

Since the outbreak of the COVID-19 pandemic, worldwide research efforts have focused on using artificial intelligence (AI) technologies on various medical data of COVID-19-positive patients in order to identify or classify various aspects…

Objective: When patients develop acute respiratory failure, accurately identifying the underlying etiology is essential for determining the best treatment. However, differentiating between common medical diagnoses can be challenging in…

Importance: An artificial intelligence (AI)-based model to predict COVID-19 likelihood from chest x-ray (CXR) findings can serve as an important adjunct to accelerate immediate clinical decision making and improve clinical decision making.…

Accurate prediction of clinical outcomes using Electronic Health Records (EHRs) is critical for early intervention, efficient resource allocation, and improved patient care. EHRs contain multimodal data, including both structured data and…

The new coronavirus disease (COVID-19) has been declared a pandemic since March 2020 by the World Health Organization. It consists of an emerging viral infection with respiratory tropism that could develop atypical pneumonia. Experts…

This paper addresses issues on cough-based COVID-19 detection. We propose a cross-dataset transfer learning approach to improve the performance of COVID-19 detection by incorporating cough detection, cough segmentation, and data…

Purpose: Since the recent COVID-19 outbreak, there has been an avalanche of research papers applying deep learning based image processing to chest radiographs for detection of the disease. To test the performance of the two top models for…

Recently, COVID-19 pandemic has rapidly evolved into a critical global health crisis, profoundly impacting daily life. As a result, CAD systems have gained significant interest for its massive computational capabilities, which facilitate…

Purpose: This study aimed to develop and validate computer-aided diagnosis (CXDx) system for classification between COVID-19 pneumonia, non-COVID-19 pneumonia, and the healthy on chest X-ray (CXR) images. Materials and Methods: From two…

The Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China, in early December 2019 and now becoming a pandemic. When COVID-19 patients undergo radiography examination, radiologists can observe the present of radiographic…

Despite the widespread testing protocols for COVID-19, there are still significant challenges in early detection of the disease, which is crucial for preventing its spread and optimizing patient outcomes. Owing to the limited testing…

Background and Objective: Artificial intelligence (AI) methods coupled with biomedical analysis has a critical role during pandemics as it helps to release the overwhelming pressure from healthcare systems and physicians. As the ongoing…