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  1. Article ; Online: Predictive Modeling Using Artificial Intelligence and Machine Learning Algorithms on Electronic Health Record Data: Advantages and Challenges.

    Patton, Michael J / Liu, Vincent X

    Critical care clinics

    2023  Volume 39, Issue 4, Page(s) 647–673

    Abstract: The rapid adoption of electronic health record (EHR) systems in US hospitals from 2008 to 2014 produced novel data elements for analysis. Concurrent innovations in computing architecture and machine learning (ML) algorithms have made rapid consumption of ...

    Abstract The rapid adoption of electronic health record (EHR) systems in US hospitals from 2008 to 2014 produced novel data elements for analysis. Concurrent innovations in computing architecture and machine learning (ML) algorithms have made rapid consumption of health data feasible and a powerful engine for clinical innovation. In critical care research, the net convergence of these trends has resulted in an exponential increase in outcome prediction research. In the following article, we explore the history of outcome prediction in the intensive care unit (ICU), the growing use of EHR data, and the rise of artificial intelligence and ML (AI) in critical care.
    MeSH term(s) Humans ; Artificial Intelligence ; Electronic Health Records ; Algorithms ; Machine Learning ; Critical Care
    Language English
    Publishing date 2023-04-26
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 1006423-0
    ISSN 1557-8232 ; 0749-0704
    ISSN (online) 1557-8232
    ISSN 0749-0704
    DOI 10.1016/j.ccc.2023.02.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Histopathology aiding diagnosis of viscerocutaneous loxoscelism in a nonendemic region.

    Mani, Smrithi / Katzman, Charles / Liu, Vincent

    JAAD case reports

    2024  Volume 45, Page(s) 11–17

    Language English
    Publishing date 2024-01-05
    Publishing country United States
    Document type Case Reports
    ZDB-ID 2834220-3
    ISSN 2352-5126
    ISSN 2352-5126
    DOI 10.1016/j.jdcr.2023.12.014
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: The future of AI in critical care is augmented, not artificial, intelligence.

    Liu, Vincent X

    Critical care (London, England)

    2020  Volume 24, Issue 1, Page(s) 673

    MeSH term(s) Algorithms ; Artificial Intelligence/standards ; Artificial Intelligence/trends ; Automobile Driving/standards ; Critical Care/standards ; Critical Care/trends ; Forecasting/methods ; Humans
    Language English
    Publishing date 2020-12-02
    Publishing country England
    Document type Editorial
    ZDB-ID 2041406-7
    ISSN 1466-609X ; 1364-8535
    ISSN (online) 1466-609X
    ISSN 1364-8535
    DOI 10.1186/s13054-020-03404-5
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  4. Article ; Online: The COVID-19 Pandemic Strikes Again and Again and Again.

    Myers, Laura C / Liu, Vincent X

    JAMA network open

    2022  Volume 5, Issue 3, Page(s) e221760

    MeSH term(s) COVID-19 ; Humans ; Pandemics ; SARS-CoV-2
    Language English
    Publishing date 2022-03-01
    Publishing country United States
    Document type Journal Article ; Comment
    ISSN 2574-3805
    ISSN (online) 2574-3805
    DOI 10.1001/jamanetworkopen.2022.1760
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  5. Article: Sezary syndrome initially presenting as pityriasis rubra pilaris: Clinicopathologic study of 3 cases.

    Alsawas, Mouaz / Alzayadneh, Eyas / Mou, Eric / Liu, Vincent

    JAAD case reports

    2023  Volume 44, Page(s) 101–106

    Language English
    Publishing date 2023-12-27
    Publishing country United States
    Document type Case Reports
    ZDB-ID 2834220-3
    ISSN 2352-5126
    ISSN 2352-5126
    DOI 10.1016/j.jdcr.2023.12.003
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  6. Article ; Online: Use of Sepsis Clinical Prediction Models to Improve Patient Care.

    Mogri, Murtaza / Grant, Richard W / Liu, Vincent X

    JAMA internal medicine

    2023  Volume 183, Issue 6, Page(s) 612–615

    MeSH term(s) Humans ; Models, Statistical ; Prognosis ; Sepsis/diagnosis ; Sepsis/therapy ; Patient Care ; Intensive Care Units
    Language English
    Publishing date 2023-04-18
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 2699338-7
    ISSN 2168-6114 ; 2168-6106
    ISSN (online) 2168-6114
    ISSN 2168-6106
    DOI 10.1001/jamainternmed.2022.7164
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  7. Article ; Online: Toward the "Plateau of Productivity": Enhancing the Value of Machine Learning in Critical Care.

    Liu, Vincent X

    Critical care medicine

    2018  Volume 46, Issue 7, Page(s) 1196–1197

    MeSH term(s) Algorithms ; Critical Care ; Humans ; Intensive Care Units ; Machine Learning
    Language English
    Publishing date 2018-06-18
    Publishing country United States
    Document type Journal Article ; Comment
    ZDB-ID 197890-1
    ISSN 1530-0293 ; 0090-3493
    ISSN (online) 1530-0293
    ISSN 0090-3493
    DOI 10.1097/CCM.0000000000003170
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  8. Article ; Online: Algorithmic prognostication in critical care: a promising but unproven technology for supporting difficult decisions.

    Weissman, Gary E / Liu, Vincent X

    Current opinion in critical care

    2021  Volume 27, Issue 5, Page(s) 500–505

    Abstract: Purpose of review: Patients, surrogate decision makers, and clinicians face weighty and urgent decisions under uncertainty in the ICU, which could be aided by risk prediction. Although emerging artificial intelligence/machine learning (AI/ML) algorithms ...

    Abstract Purpose of review: Patients, surrogate decision makers, and clinicians face weighty and urgent decisions under uncertainty in the ICU, which could be aided by risk prediction. Although emerging artificial intelligence/machine learning (AI/ML) algorithms could reduce uncertainty surrounding these life and death decisions, certain criteria must be met to ensure their bedside value.
    Recent findings: Although ICU severity of illness scores have existed for decades, these tools have not been shown to predict well or to improve outcomes for individual patients. Novel AI/ML tools offer the promise of personalized ICU care but remain untested in clinical trials. Ensuring that these predictive models account for heterogeneity in patient characteristics and treatments, are not only specific to a clinical action but also consider the longitudinal course of critical illness, and address patient-centered outcomes related to equity, transparency, and shared decision-making will increase the likelihood that these tools improve outcomes. Improved clarity around standards and contributions from institutions and critical care departments will be essential.
    Summary: Improved ICU prognostication, enabled by advanced ML/AI methods, offer a promising approach to inform difficult and urgent decisions under uncertainty. However, critical knowledge gaps around performance, equity, safety, and effectiveness must be filled and prospective, randomized testing of predictive interventions are still needed.
    MeSH term(s) Artificial Intelligence ; Critical Care ; Critical Illness ; Humans ; Prospective Studies ; Technology
    Language English
    Publishing date 2021-07-07
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 1235629-3
    ISSN 1531-7072 ; 1070-5295
    ISSN (online) 1531-7072
    ISSN 1070-5295
    DOI 10.1097/MCC.0000000000000855
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  9. Article ; Online: Keeping Score of Severity Scores: Taking the Next Step.

    Liu, Vincent

    Critical care medicine

    2016  Volume 44, Issue 3, Page(s) 639–640

    MeSH term(s) Emergency Service, Hospital ; Female ; Humans ; Infection/classification ; Male ; Severity of Illness Index
    Language English
    Publishing date 2016-03
    Publishing country United States
    Document type Comment ; Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 197890-1
    ISSN 1530-0293 ; 0090-3493
    ISSN (online) 1530-0293
    ISSN 0090-3493
    DOI 10.1097/CCM.0000000000001501
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  10. Article ; Online: Heterogeneity of Benefit from Earlier Time-to-Antibiotics for Sepsis.

    Hechtman, Rachel K / Kipnis, Patricia / Cano, Jennifer / Seelye, Sarah / Liu, Vincent X / Prescott, Hallie C

    American journal of respiratory and critical care medicine

    2024  Volume 209, Issue 7, Page(s) 852–860

    Abstract: Rationale: ...

    Abstract Rationale:
    MeSH term(s) Humans ; Shock, Septic ; Anti-Bacterial Agents/therapeutic use ; Sepsis/therapy ; Cohort Studies ; Neoplasms ; Retrospective Studies ; Hospital Mortality
    Chemical Substances Anti-Bacterial Agents
    Language English
    Publishing date 2024-01-24
    Publishing country United States
    Document type Observational Study ; Journal Article
    ZDB-ID 1180953-x
    ISSN 1535-4970 ; 0003-0805 ; 1073-449X
    ISSN (online) 1535-4970
    ISSN 0003-0805 ; 1073-449X
    DOI 10.1164/rccm.202310-1800OC
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