AIMC Topic: Anosmia

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Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study.

The Lancet. Digital health Jul 29, 2021
BACKGROUND: Self-reported symptoms during the COVID-19 pandemic have been used to train artificial intelligence models to identify possible infection foci. To date, these models have only considered the culmination or peak of symptoms, which is not s...
Middle Aged Adolescent Male Self Report Chest Pain Models, Biological Mobile Applications Young Adult Sensitivity and Specificity Adult Aged Aged, 80 and over SARS-CoV-2 Anosmia Epidemiologic Studies United Kingdom Early Diagnosis Dyspnea COVID-19 Humans Artificial Intelligence Pandemics Female Prospective Studies
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App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning.

PloS one Mar 25, 2021
BACKGROUND: Tests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of sympto...
Male False Negative Reactions Risk Middle Aged False Positive Reactions Adult COVID-19 Testing Self Report Registries Mobile Applications Fever Dyspnea Brazil Retrospective Studies Anosmia Machine Learning COVID-19 SARS-CoV-2 Female Humans
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Diagnosis of coronavirus disease 2019 and the potential role of deep learning: insights from the experience of Cairo University Hospitals.

The Journal of international medical research Jul 1, 2022
OBJECTIVES: Early detection of coronavirus disease 2019 (COVID-19) is crucial for patients and public health to ensure pandemic control. We aimed to correlate clinical and laboratory data of patients with COVID-19 and their polymerase chain reaction ...
SARS-CoV-2 COVID-19 Deep Learning Humans Neutropenia Retrospective Studies Anosmia Hospitals, University Ferritins
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