AIMC Topic: COVID-19

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Computer-aided diagnosis of chest X-ray for COVID-19 diagnosis in external validation study by radiologists with and without deep learning system.

Scientific reports
To evaluate the diagnostic performance of our deep learning (DL) model of COVID-19 and investigate whether the diagnostic performance of radiologists was improved by referring to our model. Our datasets contained chest X-rays (CXRs) for the following...

A Novel Deep Learning Model for Medical Report Generation by Inter-Intra Information Calibration.

IEEE journal of biomedical and health informatics
Automatic generation of medical reports can provide diagnostic assistance to doctors and reduce their workload. To improve the quality of the generated medical reports, injecting auxiliary information through knowledge graphs or templates into the mo...

Towards Building a Trustworthy Deep Learning Framework for Medical Image Analysis.

Sensors (Basel, Switzerland)
Computer vision and deep learning have the potential to improve medical artificial intelligence (AI) by assisting in diagnosis, prediction, and prognosis. However, the application of deep learning to medical image analysis is challenging due to limit...

The Effect of Using a Rehabilitation Robot for Patients with Post-Coronavirus Disease (COVID-19) Fatigue Syndrome.

Sensors (Basel, Switzerland)
The aim of this study was to compare the effectiveness of traditional neurological rehabilitation and neurological rehabilitation combined with a rehabilitation robot for patients with post-COVID-19 fatigue syndrome. Eighty-six participants transferr...

Using artificial intelligence algorithms to predict the overall survival of hemodialysis patients during the COVID-19 pandemic: A prospective cohort study.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Hemodialysis (HD) patients are a vulnerable population at high risk for severe complications from COVID-19. The impact of partial COVID-19 vaccination on the survival of HD patients remains uncertain. This prospective cohort study was des...

Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study.

Journal of medical Internet research
BACKGROUND: Experience-based knowledge and value considerations of health professionals, citizens, and patients are essential to formulate public health and clinical guidelines that are relevant and applicable to medical practice. Conventional method...

Deep Learning Assisted Surface-Enhanced Raman Spectroscopy (SERS) for Rapid and Direct Nucleic Acid Amplification and Detection: Toward Enhanced Molecular Diagnostics.

ACS nano
Surface-enhanced Raman scattering (SERS) has evolved into a robust analytical technique capable of detecting a variety of biomolecules despite challenges in securing a reliable Raman signal. Conventional SERS-based nucleic acid detection relies on hy...

A robust deep learning workflow to predict CD8 + T-cell epitopes.

Genome medicine
BACKGROUND: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining tolerance against self-antigens, which has sparked interest in the development of various T-cell-focus...

Artificial intelligence-enhanced electrocardiography for early assessment of coronavirus disease 2019 severity.

Scientific reports
Despite challenges in severity scoring systems, artificial intelligence-enhanced electrocardiography (AI-ECG) could assist in early coronavirus disease 2019 (COVID-19) severity prediction. Between March 2020 and June 2022, we enrolled 1453 COVID-19 p...

COVID-19 diagnosis using clinical markers and multiple explainable artificial intelligence approaches: A case study from Ecuador.

SLAS technology
The COVID-19 pandemic erupted at the beginning of 2020 and proved fatal, causing many casualties worldwide. Immediate and precise screening of affected patients is critical for disease control. COVID-19 is often confused with various other respirator...