Conventional risk prediction models fail to accurately predict mortality risk among patients with coronavirus disease 2019 in intensive care units: a difficult time to assess clinical severity and quality of care

Endo, Hideki; Ohbe, Hiroyuki; Kumasawa, Junji; Uchino, Shigehiko; Hashimoto, Satoru; Aoki, Yoshitaka; Asaga, Takehiko; Hashiba, Eiji; Hatakeyama, Junji; Hayakawa, Katsura; Ichihara, Nao; Irie, Hiromasa; Kawasaki, Tatsuya; Kurosawa, Hiroshi; Nakamura, Tomoyuki; Okamoto, Hiroshi; Takaki, Shunsuke; Takimoto, Kohei; Uchida, Masatoshi; Matsubara, Hiroaki

doi:10.1186/s40560-021-00557-5

Cited by 4 publications

(2 citation statements)

References 9 publications

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“…25% were outside their 95% confidence intervals for numbers of cases when only 5% should have been. Endo et al conclude that ‘calibration of the [mortality risk] models were poor’ (Endo et al , 2021, p. 1). See also Eker (2020); Holmdahl and Buckee (2020) and for a general overview see Cepelewicz (2021).…”

Section: Taming Failures During the Covid-19 Pandemicmentioning

confidence: 99%

Uncertainty Phobia and Epistemic Forbearance in a Pandemic

Shackel

2022

Roy. Inst. Philos. Suppl.

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In this chapter I show how challenges to our ability to tame the uncertainty of a pandemic leaves us vulnerable to uncertainty phobia. This is because, contrary to what we might hope, not all the uncertainty that matters can be tamed by our knowledge of the relevant probabilities. Unrelievable wild uncertainty is a hard burden to bear, especially so when we must act in the face of it. We are tempted to retreat into uncertainty phobia, leading to fixed definite opinions precisely when acting on sound judgement requires our opinions to be hedged and mobile. Coping with a pandemic requires us to bear the burden rather than give in to temptation: it requires us to practise the virtue of epistemic forbearance.

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Section: Taming Failures During the Covid-19 Pandemicmentioning

confidence: 99%

Uncertainty Phobia and Epistemic Forbearance in a Pandemic

Shackel

2022

Roy. Inst. Philos. Suppl.

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“…Although compartmental models are necessary for understanding the mechanisms that occur during an epidemic, it is unknown whether they are suitable for predicting prognosis [ 124 ].…”

Section: Public Healthmentioning

confidence: 99%

Application of Artificial Intelligence in COVID-19 Diagnosis and Therapeutics

Asada

Komatsu

Shimoyama

et al. 2021

JPM

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The coronavirus disease 2019 (COVID-19) pandemic began at the end of December 2019, giving rise to a high rate of infections and causing COVID-19-associated deaths worldwide. It was first reported in Wuhan, China, and since then, not only global leaders, organizations, and pharmaceutical/biotech companies, but also researchers, have directed their efforts toward overcoming this threat. The use of artificial intelligence (AI) has recently surged internationally and has been applied to diverse aspects of many problems. The benefits of using AI are now widely accepted, and many studies have shown great success in medical research on tasks, such as the classification, detection, and prediction of disease, or even patient outcome. In fact, AI technology has been actively employed in various ways in COVID-19 research, and several clinical applications of AI-equipped medical devices for the diagnosis of COVID-19 have already been reported. Hence, in this review, we summarize the latest studies that focus on medical imaging analysis, drug discovery, and therapeutics such as vaccine development and public health decision-making using AI. This survey clarifies the advantages of using AI in the fight against COVID-19 and provides future directions for tackling the COVID-19 pandemic using AI techniques.

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