• Mashup Score: 0

    April 17, 2023 — eClinicalWorks, an ambulatory cloud EHR, today announced it is advancing its intelligent cloud technology with the power of AI — keeping usability, security, and patient safety the top priority. eClinicalWorks recently committed $100 million to Microsoft Azure cloud services. This significant investment gives eClinicalWorks access to the latest innovations available with…

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    • @DAICeditor @eClinicalWorks Integration with #ChatGPT, cognitive services, and #machine_learning models will increase value to customers: https://t.co/MrXJrDSOAw #HIMSS23

  • Mashup Score: 2

    Background The sublingual microcirculation presumably exhibits disease-specific changes in function and morphology. Algorithm-based quantification of functional microcirculatory hemodynamic variables in handheld vital microscopy (HVM) has recently allowed identification of hemodynamic alterations in the microcirculation associated with COVID-19. In the present study we hypothesized that…

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    • #CritCare #OpenAccess A supervised #deep_machine_learning based model can be used to differentiate critically ill #COVID19 patients from healthy volunteers. https://t.co/ktyQt1mb8O @jlvincen @ISICEM #FOAMed #FOAMcc #Artificial_Intelligence #microcirculation #machine_learning https://t.co/4X0cButcv2

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    Thematic Series After so many negative randomized, controlled trials, that have evaluated a number of simplified therapeutic interventions that could be applied to large patient populations, people are turning their interest back to personalized medicine.This new Thematic Series will share thoughts based on scientific data and help the clinician to individualize the…

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    • #CritCare #OpenAccess TC: “#PERSONALIZED_MEDICINE IN THE #ICU” https://t.co/7fpW65fRXf How #machine_learning can improve efficiency of early #trials of new #sepsis therapies https://t.co/08KGljYZvQ @jlvincen @ISICEM #BMC #ICU #organ_failure #Thrombocytopenia #Immunoparalysis https://t.co/PPBHPd8juQ

  • Mashup Score: 2

    May 23, 2022 — New data from a study of more than 100 million hospitalizations using machine learning augmentation was presented at the Society for Cardiovascular Angiography & Interventions (SCAI) 2022 Scientific Sessions. The findings reveal percutaneous coronary intervention (PCI) is safe and increasing among cancer patients. Cardio-oncology is a field within cardiology that focuses on the…

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    • @DAICeditor @SCAI New data from a #study of more than 100 million hospitalizations using #machine_learning #augmentation was presented at #SCAI22; the findings reveal percutaneous coronary intervention (#PCI) is safe and increasing among #cancer patients: https://t.co/srjjVB4gV9

  • Mashup Score: 2
    Wolters Kluwer Health - 2 year(s) ago

    JavaScript Error JavaScript has been disabled on your browser. You must enable it to continue. Here’s how to enable JavaScript in the following browsers: Internet Explorer From the Tools menu, select Options Click the Content tab Select Enable…

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    • #CritCareExplore @SCCM Combining #machine_learning w/ HR and blood pressure waveform variability metrics, clinical features, and physician prediction can help predict time to death after the withdrawal of life supporting measures in the ICU. https://t.co/S9mMuzLgqt https://t.co/IIQjmsotmi

  • Mashup Score: 1

    Background Timely recognition of hemodynamic instability in critically ill patients enables increased vigilance and early treatment opportunities. We develop the Hemodynamic Stability Index (HSI), which highlights situational awareness of possible hemodynamic instability occurring at the bedside and to prompt assessment for potential hemodynamic interventions. Methods We used an ensemble of…

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    • #CritCare #OpenAccess Timely recognition of #hemodynamic instability in critically ill patients by using #machine_learning https://t.co/80CXsmOUZt #FOAMed #FOAMcc #BMC #ICU #IntensiveCare #artificial_intelligence #vasoactive #cardiovascular @jlvincen @ISICEM https://t.co/miGuJVhBhL

  • Mashup Score: 1

    Background Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine learning model, based on retrospective & prospective clinical data, to stratify patient risk and predict ICU survival and outcomes. Methods A…

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    • #CritCare #OA A #machine_learning model to predict #clinical_risks, #ICU survival and outcomes of #COVID19 patients https://t.co/fiIHTvxx6N #FOAMed #FOAMcc #BMC @ISICEM @jlvincen #prognosis #ARDS #respiratory_failure #infection #pandemics #Sars_CoV_2 https://t.co/N2xPND1apx

  • Mashup Score: 1

    Background Usually, arterial oxygenation in patients with the acute respiratory distress syndrome (ARDS) improves substantially by increasing the level of positive end-expiratory pressure (PEEP). Herein, we are proposing a novel variable [PaO2/(FiO2xPEEP) or P/FPE] for PEEP ≥ 5 to address Berlin’s definition gap for ARDS severity by using machine learning (ML) approaches. Methods We examined…

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    • #CritCare #OpenAccess EDITOR’S PICK https://t.co/ohQ4uFoB0Z  A #MACHINE_LEARNING APPROACH TO ASSESS #ARDS SEVERITY #FOAMed #FOAMcc #BMC #ICU #Lung #respiratory_failure #prediction_model #ventilation @jlvincen @ISICEM https://t.co/bJzClNrnl7

  • Mashup Score: 5

    Background Usually, arterial oxygenation in patients with the acute respiratory distress syndrome (ARDS) improves substantially by increasing the level of positive end-expiratory pressure (PEEP). Herein, we are proposing a novel variable [PaO2/(FiO2xPEEP) or P/FPE] for PEEP ≥ 5 to address Berlin’s definition gap for ARDS severity by using machine learning (ML) approaches. Methods We examined…

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    • CritCare #OA Adressing #ARDS severity by using a #machine_learning approach https://t.co/YXDpYL2GHU #FOAMed #FOAMcc #BMC #ICU #Lung #respiratory_failure #prediction_model @ISICEM @jlvincen https://t.co/xIEGLv7Qps