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C27 Predicting Cardiothoracic Intensive Care Unit (CTICU) Readmission or Mortality...

George Cortina
PhD at Duke University
+ 12 speakers
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Machine Learning for Healthcare
August 8, 2020, Online, Los Angeles, CA, USA
Machine Learning for Healthcare
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About speakers

George Cortina
PhD at Duke University
Shujin Zhong
Data Analyst Intern at Duke Institute for Health Innovation
Marshall Nichols
Senior IT & Analytics Manager at Duke Institute for Health Innovation
Michael Gao
Data Science Lead at Duke Institute for Health Innovation
William Ratliff
Innovation Program Manager at Duke University Health System
Will Knechtle
ДолжностьInnovation Program Manager, Duke Institute for Health Innovation at Duke University Health System
Suresh Balu
Program Director at Duke School of Medicine
Kelly Kester
Clinical Operations Director at Duke University Health System
Mary Lindsay
Registered nurse at Duke University
Jill Engel
Associate Vice President - Heart Operations, Nursing & Patient Care Services at Duke University Health System
Ricardo Henao
Assistant Professor in Biostatistics and Bioinformatics at Duke University
Mark Sendak
Population Health & Data Science Lead at Duke Institute for Health Innovation
Mihai Podgoreanu
Anesthesiologist, Critical Care Specialist at Duke University

Marshall is a Data Engineer at DIHI who helps design, develop, and implement modern software solutions to complex clinical problems. These solutions include everything from automated EHR data curation to deploying real-time machine learning models for clinical staff consumption and point-of-care impact. He leverages DevOps principles to ensure that these solutions are efficient to manage, deploy and enhance. Prior to joining DIHI in 2017, Marshall worked as a bioinformatician with Duke’s Center for Applied Genomics & Precision Medicine and ran Molecular Biology wetlabs investigating the human ‘omics response to infection. He completed his BS in Biochemistry at North Carolina State University and a Masters in Biology at East Carolina University. Marshall is passionate about writing elegant code that improves the lives of others. He enjoys solving incredibly difficult problems with amazing people over a great cup of Idido from Counter Culture Coffee.

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I'm a Data Enthusiast who is interested in leveraging modern computing tools and statistical/machine learning approaches to solve problems in health care, technology, and beyond. My areas of focus include statistical software, bayesian inference, machine learning, and implementation of such methods into real-world operational settings.

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I am currently an Innovation Program Manager at The Duke Institute for Health Innovation. As part of Duke University and Duke University Health System, DIHI connects broad expertise and resources across Duke to effectively address important health care challenges and pilot innovative health care projects. Previously, I was a Consultant with Optum Advisory Services (formerly The Advisory Board). In this role, I helped lead projects focused on improving operations and reducing costs for health systems. I graduated from Duke University's Fuqua School of Business with a Health Sector Management Certificate in May of 2017. Before Fuqua, I spent 5 years in health care consulting with Cumberland Consulting Group, specializing in clinical process optimization and health IT system project design and implementation. I'm motivated by the desire to help health care providers overcome strategic and operational barriers to deliver the highest quality of care to patients.

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I am a Program Manager at the Duke Institute for Health Innovation (DIHI). DIHI catalyzes transformative innovations in health and health care through implementation of high-impact innovations, leadership development, and cultivation of a community of entrepreneurship. My career began with 6.5 years interweaving public health, health services research, and international development. As a Duke biology undergrad, my interest in how organisms work expanded to a fascination with how organizations work. I wanted to understand and fix unjust and broken systems. This passion, with values of service and close-knit community learned from my family and Wisconsin neighbors, led me to join the Peace Corps. Peace Corps service in Niger taught me to listen first and establish credibility through character and commitment. Afterwards, the Emory RSPH and Surgery Dept taught me to develop and test theories. Finally, Duke's Fuqua School of Business helped me develop business acumen, join credible networks, build proactive teams, and apply theory to practice. I work in the healthcare sector to help people directly, join smart altruistic teams, and repair complex systems. My interdisciplinary teams have improved healthcare outcomes, patient flow, access, utilization, hospital input costs, and revenue cycle management. I specialize in supporting and driving early healthcare ventures from concept to implementation, often incorporating care redesign, dashboards, telemedicine, AI, and digital heal

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Suresh Balu serves as Associate Dean for Innovation and Partnership for the School of Medicine and as Program Director, for the Duke Institute for Health Innovation (DIHI). Suresh’s experience prior to Duke spans academia, management consulting, venture capital and private equity. As a corporate and competitive strategy consultant, Suresh worked with leading life sciences and technology firms to develop strategies for innovation, revenue generation, organizational restructuring and product portfolio planning. His PE/VC experiences include product and technology due diligence, deal structuring and portfolio company management. As an entrepreneur, Suresh was responsible for program management, market and product strategy at a venture-funded firm that focused on visualization and diagnostic products. Suresh has operational and business development experience in Asia and Europe, where he helped to establish sales channels serving government and academic clients. He is an inventor named on more than 20 US and international patents. Suresh holds MS (Computer Science) and MBA (Corporate Finance) degrees as well as a Master’s degree in Informatics and Bachelor’s degree in Engineering.

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Ricardo is a respected expert in machine learning. He serves as Assistant Professor in Biostatistics and Bioinformatics at Duke University and is a member of the Duke Clinical Research Institute. He also regularly serves as a reviewer for journals such as the Journal of Machine Learning Research, Journal of Biomedical Informatics, and many others.He has coauthored more than 50 academic papers in fields such as machine learning, biostatistics, neuroscience, cancer and infectious disease.

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Mark Sendak is the Population Health & Data Science Lead at the Duke Institute for Health Innovation, where he leads interdisciplinary teams of data scientists, clinicians, and machine learning experts to build technologies that solve real clinical problems within Duke Health. He has built tools to support Duke's first adult high-utilizerprogram, chronic disease management within a Medicare Accountable Care Organization, and inpatient deterioration management. He leads a medical student innovation scholarship and is focused on building the technology infrastructure and training the workforce required to bring medicine into a new digital age. He has published in both technical venues, including Uncertainty and Artificial Intelligence and the Journal of Machine Learning Research, as well as clinical venues, including eGEMS, PlOS Medicine, and the Journal of Applied Clinical Informatics. He has worked with the National Institutes of Health (NIH) to develop a financial model for using health information technology to improve chronic kidney disease management as well as the American Medical Association (AMA) to advise on reimbursement mechanisms for artificial intelligence in healthcare. He obtained his Bachelors of Science in Mathematics from UCLA, Masters of Public Policy with a focus on health policy from Duke, and MD from Duke University School of Medicine.

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Hello, everyone. My name is Jorge Cortina and I'm in anesthesia resident at Duke University and I am sharing our work on building an early-warning model to predict the risk of post thoracic surgery. Patients decompensating hiring return the cardiothoracic. Now, the reason that we focused our model on cardiothoracic, Su patients do the complexity of their surgeries and also the Acuity of their disease. Now, typically it is our hope that patients undergoing. The surgery go

through a pattern of admission to an intermediate or step-down unit that are even lower acuity. Just thank you, diagram, for patients that decompensated after cardiothoracic surgery. Is decompensation both increases the length of the hospital, stay and also the cost in morbidity. Therefore, we felt sought to build a model that would predict the hourly risk returning to the Wilder and he stepped out hourly. when does alarm goes off, this model is based on two types of data first. There would be static or unchanging data for these patients while at least

demographics. Then every our orders lab values in BIOS. Play Mary models, have outperformed traditional score based on early warning system. Models based on two types of architecture, logistic regression around 4 and then a CPR might want to use Force. We're currently evaluating the performance of other models based on different. Additionally, we're looking at your new ways to evaluate the performance bottles, that would relate to how they would be. Is our hope to this model to start a silent run on some floors at Duke University and then

moved. Thank you very much.

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George Cortina
Shujin Zhong
Marshall Nichols
Michael Gao
William Ratliff
Will Knechtle
Suresh Balu
Kelly Kester
Mary Lindsay
Jill Engel
Ricardo Henao
Mark Sendak
Mihai Podgoreanu