In this paper, we have trained several deep convolutional networks with introduced training techniques for classifying X-ray images into three classes: normal, pneumonia, and COVID-19, based on two open-source datasets. Our data contains 180 X-ray images that belong to persons infected with COVID-19, and we attempted to apply methods to achieve the best possible results.…
Informatics in Medicine Unlocked Template
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About the Informatics in Medicine Unlocked format
Informatics in Medicine Unlocked is a peer-reviewed journal published by Elsevier, covering Computational Drug Discovery Methods, AI in cancer detection, COVID-19 diagnosis using AI.
| Publisher | Elsevier |
|---|---|
| Reference style | Numbered (Elsevier) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, C. Lee, A representative article title, Informatics in Medicine Unlocked 12 (2023) 45–58.
Formats any DOI in Informatics in Medicine Unlocked style. No sign-up. |
| Publishes research in | Computational Drug Discovery Methods AI in cancer detection COVID-19 diagnosis using AI Artificial Intelligence in Healthcare Machine Learning in Healthcare |
| ISSN | 2352-9148 |
| Citation impact (2-yr) | 8.03 |
| h-index | 91 |
| i10-index | 817 |
| Total citations | 40,414 |
| Article processing charge | $1,400 |
| Open access | Yes |
| Top institutions publishing here | Imam Abdulrahman Bin Faisal University |
| Journal website | www.journals.elsevier.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Papers published in Informatics in Medicine Unlocked per year
Citation impact of Informatics in Medicine Unlocked by publication year
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Most-cited papers in Informatics in Medicine Unlocked
Machine learning involves artificial intelligence, and it is used in solving many problems in data science. One common application of machine learning is the prediction of an outcome based upon existing data. The machine learns patterns from the existing dataset, and then applies them to an unknown dataset in order to predict the outcome. Classification…
Nowadays, automatic disease detection has become a crucial issue in medical science due to rapid population growth. An automatic disease detection framework assists doctors in the diagnosis of disease and provides exact, consistent, and fast results and reduces the death rate. Coronavirus (COVID-19) has become one of the most severe and acute diseases in recent…
Diabetic Retinopathy (DR) is a common complication of diabetes mellitus, which causes lesions on the retina that effect vision. If it is not detected early, it can lead to blindness. Unfortunately, DR is not a reversible process, and treatment only sustains vision. DR early detection and treatment can significantly reduce the risk of vision loss.…
BACKGROUND: The inability to test at scale has become humanity's Achille's heel in the ongoing war against the COVID-19 pandemic. A scalable screening tool would be a game changer. Building on the prior work on cough-based diagnosis of respiratory diseases, we propose, develop and test an Artificial Intelligence (AI)-powered screening solution for COVID-19 infection that…