[HTML][HTML] Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning

J Yang, AAS Soltan, DW Eyre, DA Clifton - Nature Machine Intelligence, 2023 - nature.com
As models based on machine learning continue to be developed for healthcare applications,
greater effort is needed to ensure that these technologies do not reflect or exacerbate any …

Risk of hospital admission with coronavirus disease 2019 in healthcare workers and their households: nationwide linkage cohort study

ASV Shah, R Wood, C Gribben, D Caldwell, J Bishop… - bmj, 2020 - bmj.com
Objective To assess the risk of hospital admission for coronavirus disease 2019 (covid-19)
among patient facing and non-patient facing healthcare workers and their household …

[HTML][HTML] An adversarial training framework for mitigating algorithmic biases in clinical machine learning

J Yang, AAS Soltan, DW Eyre, Y Yang… - NPJ digital medicine, 2023 - nature.com
Abstract Machine learning is becoming increasingly prominent in healthcare. Although its
benefits are clear, growing attention is being given to how these tools may exacerbate …

[HTML][HTML] Real-life clinical sensitivity of SARS-CoV-2 RT-PCR test in symptomatic patients

E Kortela, V Kirjavainen, MJ Ahava, ST Jokiranta… - PloS one, 2021 - journals.plos.org
Background Understanding the false negative rates of SARS-CoV-2 RT-PCR testing is
pivotal for the management of the COVID-19 pandemic and it has implications for patient …

Recent updates on liposomal formulations for detection, prevention and treatment of coronavirus disease (COVID-19)

NDFM Faizal, MCIM Amin - International journal of pharmaceutics, 2023 - Elsevier
The unprecedented outbreak of severe acute respiratory syndrome-2 (SARS-CoV-2)
worldwide has rendered it one of the most notorious pandemics ever documented in human …

[HTML][HTML] A comparative study of multiple neural network for detection of COVID-19 on chest X-ray

A Shazia, TZ Xuan, JH Chuah, J Usman, P Qian… - EURASIP journal on …, 2021 - Springer
Coronavirus disease of 2019 or COVID-19 is a rapidly spreading viral infection that has
affected millions all over the world. With its rapid spread and increasing numbers, it is …

Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings

B Cleary, JA Hay, B Blumenstiel, M Harden… - Science translational …, 2021 - science.org
Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-
2) containment, but many settings face severe limitations on testing. Group testing offers a …

Recent findings and applications of biomedical engineering for COVID-19 diagnosis: a critical review

LM Bui, H Thi Thu Phung, TT Ho Thi, V Singh… - …, 2021 - Taylor & Francis
ABSTRACT COVID-19 is one of the most severe global health crises that humanity has ever
faced. Researchers have restlessly focused on developing solutions for monitoring and …

[HTML][HTML] Sharing a household with children and risk of COVID-19: a study of over 300 000 adults living in healthcare worker households in Scotland

R Wood, E Thomson, R Galbraith, C Gribben… - Archives of disease in …, 2021 - adc.bmj.com
Objective Children are relatively protected from COVID-19, due to a range of potential
mechanisms. We investigated if contact with children also affords adults a degree of …

[HTML][HTML] Generalizability assessment of AI models across hospitals in a low-middle and high income country

J Yang, NT Dung, PN Thach, NT Phong… - Nature …, 2024 - nature.com
The integration of artificial intelligence (AI) into healthcare systems within low-middle income
countries (LMICs) has emerged as a central focus for various initiatives aiming to improve …