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covid19 [2020/07/01 12:48] jdposada |
covid19 [2020/08/20 11:47] nigam |
- [[https://medium.com/@nigam/an-ehr-derived-summary-of-the-presenting-symptoms-of-patients-screened-for-sars-cov-2-910ceb1b22b9|An EHR derived summary of presenting symptoms of patients screened for SARS-CoV-2]], data at [[http://tinyurl.com/symptom-profile|http://tinyurl.com/symptom-profile]] | - [[https://medium.com/@nigam/an-ehr-derived-summary-of-the-presenting-symptoms-of-patients-screened-for-sars-cov-2-910ceb1b22b9|An EHR derived summary of presenting symptoms of patients screened for SARS-CoV-2]], data at [[http://tinyurl.com/symptom-profile|http://tinyurl.com/symptom-profile]] |
- [[https://jamanetwork.com/journals/jama/fullarticle/2764787|High co-infection rates in COVID-19]], //in JAMA// | - [[https://jamanetwork.com/journals/jama/fullarticle/2764787|High co-infection rates in COVID-19]], //in JAMA// |
- [[https://www.medrxiv.org/content/10.1101/2020.04.19.20072017v2|Counts of hospitalized patients are a better metric for health system capacity planning for a reopening]], //accepted in JAMIA// | - [[https://academic.oup.com/jamia/article/27/7/1026/5858301|Counts of hospitalized patients are a better metric for health system capacity planning for a reopening]], //in JAMIA// |
- [[https://www.sciencedirect.com/science/article/pii/S1386653220302195|Persistent detection of SARS-CoV-2 RNA in patients and healthcare workers with COVID-19]], // in the Journal of Clinical Virology// | - [[https://www.sciencedirect.com/science/article/pii/S1386653220302195|Persistent detection of SARS-CoV-2 RNA in patients and healthcare workers with COVID-19]], // in the Journal of Clinical Virology// |
- [[https://www.medrxiv.org/content/10.1101/2020.05.03.20089151v1|Frequency of discordant SARS-CoV-2 test results among initially negative patients]]// in Clinical Infectious Diseases // | - [[https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7274223/|Occurrence and timing of subsequent SARS-CoV-2 RT-PCR positivity among initially negative patients]]// in Clinical Infectious Diseases // |
- [[https://docs.google.com/document/d/1b4QCweo6EmLYqsVSdnaTW0AJMmoPM-of3cO5yTpIOxg/edit#heading=h.gjdgxs|Estimating the feasibility of symptom based screening of COVID19]], //accepted in npj Digital Medicine // | - [[https://www.nature.com/articles/s41746-020-0300-0|Estimating the feasibility of symptom based screening of COVID19]],// in npj Digital Medicine // |
- [[https://doi.org/10.1016/j.jcv.2020.104502|A predictive tool for identification of SARS-CoV-2 PCR-negative patients using routine test results]], // in the Journal of Clinical Virology// | - [[https://doi.org/10.1016/j.jcv.2020.104502|A predictive tool for identification of SARS-CoV-2 PCR-negative patients using routine test results]], // in the Journal of Clinical Virology// |
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- [[https://www.medrxiv.org/content/10.1101/2020.04.22.20074336v1|An international characterisation of patients hospitalised with COVID-19 and a comparison with those hospitalised with influenza]], [[https://github.com/ohdsi-studies/Covid19HospitalizationCharacterization| Protocol]] and, [[https://data.ohdsi.org/Covid19CharacterizationHospitalization/| Shiny App]] | - [[https://www.medrxiv.org/content/10.1101/2020.04.22.20074336v1|An international characterisation of patients hospitalised with COVID-19 and a comparison with those hospitalised with influenza]], [[https://github.com/ohdsi-studies/Covid19HospitalizationCharacterization| Protocol]] and, [[https://data.ohdsi.org/Covid19CharacterizationHospitalization/| Shiny App]] |
- Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS). [[https://github.com/ohdsi-studies/Covid19CharacterizationCharybdis| Study Package]] and, [[https://data.ohdsi.org/Covid19CharacterizationCharybdis/| Shiny App]] | - Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS). [[https://github.com/ohdsi-studies/Covid19CharacterizationCharybdis|Study Package]] and, [[https://data.ohdsi.org/Covid19CharacterizationCharybdis/| Shiny App]] |
- A networked study investigating the association of ACEis and ARBSs on COVID-19 incidence and complications. [[https://github.com/ohdsi-studies/Covid19EstimationRasInhibitors|Protcol]] | - A networked study investigating the association of ACEis and ARBSs on COVID-19 incidence and complications. [[https://github.com/ohdsi-studies/Covid19EstimationRasInhibitors|Protcol]] |
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| {{youtube>4WRYTYfixKs?small&start=73 | Modeling for COVID-19}} |
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| 5 min clip on how we need to improve the quality of the inputs to our COVID-19 models. |
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| {{youtube>lxFBknzm88s?small | Data Science Response to a Pandemic}} |
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| A talk about Stanford's data science efforts at COVID-19 and AI: A Virtual Conference by Stanford HAI. |
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