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Seth Besmertnik
CEO at Conductor
advertising, amazon (company), c3 2020, c3ny, click-through rate, competitive advantage, conductor, content, content marketing, curiosity, digital marketing, digital marketing tips, dinosaur, entertainment, google chrome, html, innovation, internet, johns hopkins all children's hospital, market share, meta element, metadata, real-time computing, search engine, search engine optimization, sem, seo, social media, virtual keynote, web browser, website, world wide web, youtube
Brittany Casey
Pediatric Hospital Medicine Fellow at Johns Hopkins All Children’s Hospital
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
Paola Dees
Physician at Johns Hopkins All Children's Hospital
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
John Morrison
Assistant Professor of Pediatrics at The Johns Hopkins University School of Medicine
attention, breathing, communication, deep learning, electronic health record, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical record, neural network, patient, pediatrics, point of care, positive and negative predictive values, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, truth
Nicola Disma
Director of Unit for Research & InnovationConsultant paediatric Anaesthetist at IRCCS Ospedale Pediatrico Giannina Gaslini
analytics, anesthesia, bayesian inference, census, child, decision tree, demography, disability, health care, hospital, information, johns hopkins all children's hospital, learning, machine learning, medical history, music, neurology, patient, pediatrics, perioperative, prediction, predictive modelling, risk, surgery, visual analytics
Walid Habre
Head Anesthesiological Investigations Unit at Université de Genève
analytics, anesthesia, bayesian inference, census, child, decision tree, demography, disability, health care, hospital, information, johns hopkins all children's hospital, learning, machine learning, medical history, music, neurology, patient, pediatrics, perioperative, prediction, predictive modelling, risk, surgery, visual analytics
Mohamed Rehman
Eric Kobren Professor of Applied Health Informatics at The Johns Hopkins University School of Medicine
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Luis Ahumada
ДолжностьDirector Center for Pediatric Data Science and Analytic Methodology at Johns Hopkins All Children's Hospital
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Ali Jalali
Senior Data Scientist at Biofourmis
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
Hannah Lonsdale
Clinical Research Associate at The Johns Hopkins University
analytics, anesthesia, attention, bayesian inference, breathing, census, child, communication, decision tree, deep learning, demography, disability, electronic health record, health care, hospital, hospital medicine, hospital readmission, information, intuition, johns hopkins all children's hospital, learning, machine learning, medical history, medical record, music, neural network, neurology, patient, pediatrics, perioperative, point of care, positive and negative predictive values, prediction, predictive modelling, risk, risk assessment, sample size determination, sensitivity and specificity, surgery, truth, visual analytics
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