AIMC Topic: COVID-19

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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...

Coot-Lion optimized deep learning algorithm for COVID-19 point mutation rate prediction using genome sequences.

Computer methods in biomechanics and biomedical engineering
In this study, a deep quantum neural network (DQNN) based on the Lion-based Coot algorithm (LBCA-based Deep QNN) is employed to predict COVID-19. Here, the genome sequences are subjected to feature extraction. The fusion of features is performed usin...

Assessment of routine same-day discharge surgery for robot-assisted radical prostatectomy.

World journal of urology
INTRODUCTION: It is important for robotic surgery to be cost-effective, especially by reducing the length of stay (LOS). Therefore, we developed a protocol for day-case robot-assisted radical prostatectomy (RARP). This study aimed to validate this as...

Automatic transparency evaluation for open knowledge extraction systems.

Journal of biomedical semantics
BACKGROUND: This paper proposes Cyrus, a new transparency evaluation framework, for Open Knowledge Extraction (OKE) systems. Cyrus is based on the state-of-the-art transparency models and linked data quality assessment dimensions. It brings together ...

Fully Automatic Dual-Probe Lung Ultrasound Scanning Robot for Screening Triage.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Two-dimensional lung ultrasound (LUS) has widely emerged as a rapid and noninvasive imaging tool for the detection and diagnosis of coronavirus disease 2019 (COVID-19). However, image differences will be magnified due to changes in ultrasound (US) im...

A separable temporal convolutional networks based deep learning technique for discovering antiviral medicines.

Scientific reports
An alarming number of fatalities caused by the COVID-19 pandemic has forced the scientific community to accelerate the process of therapeutic drug discovery. In this regard, the collaboration between biomedical scientists and experts in artificial in...