Preferences for Artificial Intelligence Clinicians Before and During the COVID-19 Pandemic: Discrete Choice Experiment and Propensity Score Matching StudyOriginal Paper Published on 2021-03-022022-10-30 Journal: Journal of Medical Internet Research [Category] Coronavirus, SARS, [키워드] 95% CI Accuracy affected Analysis artificial artificial intelligence attribute can be used Care caused changes in choice clinical diagnose clinician clinician diagnosis COVID-19 COVID-19 pandemic demographic characteristics diagnose diagnoses Diagnosis Discrete discrete choice discrete latent traits female group Health high accuracy intelligence latent class logit male matching objective Odds ratio pandemic Patient Patients’ preferences preference propensity score matching public health questionnaire receive receiving recruited remained resource respondent Result score Sex stratified Traditional medicine were used [DOI] 10.2196/26997 PMC 바로가기 [Article Type] Original Paper
Patients’ Preferences for Artificial Intelligence Applications Versus Clinicians in Disease Diagnosis During the SARS-CoV-2 Pandemic in China: Discrete Choice ExperimentOriginal Paper Published on 2021-02-232022-10-30 Journal: Journal of Medical Internet Research [Category] COVID-19, MERS, [키워드] 95% CI Accuracy Analysis Anxiety app application applied approach artificial artificial intelligence attribute attributes calculate Care China choice clinician Clinicians coefficients collected data contribute COVID-19 COVID-19 epidemic data sets Diagnosis diagnostic Diagnostic method dimension Discrete discrete choice experiment Effect experiment Factor Follow-up growth Health help heterogeneous highest human clinicians increase intelligence Latent latent class latent-class conditional logit logit main analysis management Misdiagnosis multinomial logit analysis objective Odds ratio p value pandemic Patient Patient preference preference questionnaire Result SARS-CoV-2 standard error the SARS-CoV-2 utility [DOI] 10.2196/22841 PMC 바로가기 [Article Type] Original Paper
Socioeconomic factors analysis for COVID-19 US reopening sentiment with Twitter and census dataResearch Article Published on 2021-02-062022-10-31 Journal: Heliyon [Category] COVID-19, [키워드] Accuracy Analysis association binary Binary logit model census changes in Characteristics collected conditions coronavirus COVID-19 Depression directional emotional employment Factor Guidance identify IMPROVE indicate less lockdown policies logit media mitigate pandemic Pearson positive provide Reopen representing researchers resources sentiment analysis state the United State trauma Travel Twitter was collected was used Washington [DOI] 10.1016/j.heliyon.2021.e06200 PMC 바로가기 [Article Type] Research Article
A biomarker based severity progression indicator for COVID-19: the Kuwait prognosis indicator scoreCOVID-19에 대한 바이오마커 기반 중증도 진행 지표: 쿠웨이트 예후 지표 점수Article Published on 2020-12-012022-08-31 Journal: Biomarkers : biochemical indicators of exposure, r [Category] MERS, SARS, 바이오마커, [키워드] acute respiratory distress acute respiratory distress syndrome adverse outcome age albumin Biomarker calculated calculator calibration Clinical course collected consecutive patient Course COVID-19 COVID-19 disease criterion CRP dataset death defined demonstrated Diagnosis disease severity Final Health Health policy Hospital admission Inclusion independent predictor independent predictors Infection Kuwait logit lymphocyte Mild monocyte Mortality Most patients Patient PCR percentage Pneumonia predict primary endpoint procalcitonin Prognosis prognostic model progression recruited resources respiratory distress risk serum albumin severe COVID-19 severe COVID-19 disease severity syndrome the disease variable with COVID-19 worldwide pandemic Wuhan Wuhan, China [DOI] 10.1080/1354750X.2020.1841296 PMC 바로가기 [Article Type] Article
Mortality and other adverse outcomes in patients with type 2 diabetes mellitus admitted for COVID-19 in association with glucose-lowering drugs: a nationwide cohort studyResearch Article Published on 2020-11-162022-10-28 Journal: BMC Medicine [Category] COVID-19, SARS, [키워드] 1:1 accompany Admission adverse outcome adverse outcomes association Characteristics cohort of patient cohort study Combination Coronavirus disease 2019 COVID-19 COVID-19 patient diabete Dipeptidyl peptidase-4 drugs evaluate evaluated Evidence Glucose-lowering drug hospital Hospital stay ICU admission In-hospital in-hospital complication In-hospital death information inhibitor inhibitors insulin intensive care internal invasive Limited Logistic regression logit mechanical ventilation monotherapy Mortality multicenter Non-invasive outcome Patient patients with COVID-19 propensity score matching Prospective Study registry Result Sample size selected Society Spain Spanish standardized mean difference study outcomes Treatment type 2 diabete Type 2 diabetes mellitus were used [DOI] 10.1186/s12916-020-01832-2 PMC 바로가기 [Article Type] Research Article
Public preference for COVID‐19 vaccines in China: A discrete choice experimentOriginal Research Paper Published on 2020-10-062022-11-01 Journal: Health Expectations : An International Journal of Public Participation in Health Care and Health Policy [Category] COVID-19, MERS, [키워드] Administered adverse event Affect affecting Analysis asked attribute calculated Characteristics China Chinese Chinese public coronavirus disease COVID‐19 COVID‐19 pandemic develop discrete choice experiment effective vaccine Effectiveness experiment Factor General population globe group discussion hypothetical identify information logit pandemic participant participated preference Protective provided Public Regression model response Result the vaccine vaccination Vaccination strategy Vaccine was used Willingness to pay [DOI] 10.1111/hex.13140 PMC 바로가기 [Article Type] Original Research Paper
Are we all in this together? Longitudinal assessment of cumulative adversities by socioeconomic position in the first 3 weeks of lockdown in the UKOriginal Research Published on 2020-09-012022-10-29 Journal: Journal of epidemiology and community health [Category] Coronavirus, SARS, [키워드] adverse event age analysed Cohort studies collected coronavirus disease country COVID-19 COVID-19 pandemic Covid-19 social study cumulative cut in discrepancy employment Epidemiology Gender group inequality less lockdown logit longitudinal measure media medications mental health pandemic participant Poisson proportion Psychosocial factors public health reduce reductions in Result shown University College London virus [DOI] 10.1136/jech-2020-214475 PMC 바로가기 [Article Type] Original Research