Keynote Speakers :: ConferenceCast.tv

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