A review on deep learning techniques for the diagnosis of novel coronavirus (COVID-19)
Novel coronavirus (COVID-19) outbreak, has raised a calamitous situation all over the world
and has become one of the most acute and severe ailments in the past hundred years. The …
and has become one of the most acute and severe ailments in the past hundred years. The …
[HTML][HTML] Artificial intelligence in the fight against COVID-19: scoping review
Background In December 2019, COVID-19 broke out in Wuhan, China, leading to national
and international disruptions in health care, business, education, transportation, and nearly …
and international disruptions in health care, business, education, transportation, and nearly …
COVID-19 prediction and detection using deep learning
Currently, the detection of coronavirus disease 2019 (COVID-19) is one of the main
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
challenges in the world, given the rapid spread of the disease. Recent statistics indicate that …
[HTML][HTML] Development and validation of a prediction model for severe respiratory failure in hospitalized patients with SARS-CoV-2 infection: a multicentre cohort study …
M Bartoletti, M Giannella, L Scudeller… - Clinical Microbiology …, 2020 - Elsevier
Objectives We aimed to develop and validate a risk score to predict severe respiratory
failure (SRF) among patients hospitalized with coronavirus disease-2019 (COVID-19) …
failure (SRF) among patients hospitalized with coronavirus disease-2019 (COVID-19) …
Targeted validation: validating clinical prediction models in their intended population and setting
Clinical prediction models must be appropriately validated before they can be used. While
validation studies are sometimes carefully designed to match an intended population/setting …
validation studies are sometimes carefully designed to match an intended population/setting …
[HTML][HTML] CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification
The current COVID-19 pandemic overloads healthcare systems, including radiology
departments. Though several deep learning approaches were developed to assist in CT …
departments. Though several deep learning approaches were developed to assist in CT …
Statistical analysis of clinical COVID-19 data: a concise overview of lessons learned, common errors and how to avoid them
M Wolkewitz, J Lambert, M von Cube… - Clinical …, 2020 - Taylor & Francis
By definition, in-hospital patient data are restricted to the time between hospital admission
and discharge (alive or dead). For hospitalised cases of COVID-19, a number of events …
and discharge (alive or dead). For hospitalised cases of COVID-19, a number of events …
A novel specific artificial intelligence-based method to identify COVID-19 cases using simple blood exams
Background The SARS-CoV-2 virus responsible for COVID-19 poses a significant challenge
to healthcare systems worldwide. Despite governmental initiatives aimed at containing the …
to healthcare systems worldwide. Despite governmental initiatives aimed at containing the …
[HTML][HTML] Lobar distribution of COVID-19 pneumonia based on chest computed tomography findings; a retrospective study
Methods: This was a retrospective study performed on 63 Iranian adult patients with a final
diagnosis of COVID-19. All patients had undergone chest CT scan on admission …
diagnosis of COVID-19. All patients had undergone chest CT scan on admission …
Factores asociados a la hospitalización de pacientes con COVID-19 en la Unidad de Cuidados Intensivos de una clínica en 2020
Y Lozano, EV Palacios - Horizonte Médico (Lima), 2021 - scielo.org.pe
Objetivo: Identificar los factores asociados a la hospitalización de los pacientes con COVID-
19 en una unidad de cuidados intensivos. Materiales y métodos: Estudio observacional …
19 en una unidad de cuidados intensivos. Materiales y métodos: Estudio observacional …