MiCHAMP Seminar Series

The Seminar Series is designed to reflect the rich multidisciplinary and collaborative nature of MiCHAMP, with membership from Medicine, Engineering, Statistics, Nursing, Public Health and Pharmacy at U-M and other institutions. Discussion is highly encouraged and trainees are welcome to attend with their faculty mentors.

We are collaborating with Duke University, Tufts University and Mayo Clinic on the Big Data and AI in Health Seminar Series. We will alternate between this new series and the smaller, U-M only MiCHAMP Seminar Series.

All seminars will be via Zoom. Anyone is welcome to join the events for the Big Data and AI in Health Seminar Series. Invites to the U-M only seminars will be sent to members’ emails the week of the presentation.

Select seminars are available in our YouTube playlist.

Upcoming Seminars

Spring 2024 Seminars

5/17/24 – Big Data & AI in Health Seminar presented by Mayo Clinic

Past Seminars

Friday April 19, 2024

Dr. Mike Burns, UM

AI for Hospital Operations and Revenue Cycle: Mastering Margins with Machine Intelligence

Thursday April 4, 2024

Dr. Rohan Khera, Yale


Friday March 15, 2024, 2-3pm

Sharad Goel, PhD, Harvard University

Everything But The Kitchen Sink

Location: Zoom | 12345

Friday March 1, 2024

Bob Jones, Executive Director, Emerging Technology, ITS,UM

& Caleb Smith, OoR, UM

Generative AI Tools for Research: What Researchers need to know about UM GPT, Maizey, and beyond…

Friday February 16, 2024

Sarah Jabbour,PhD Candidate, Computer Science and Engineering,MLD3 Lab, Fouhey AI Lab,UM

& Michael Sjoding, MD, MSC, Pulmonary and Critical Care Medicine, UM

AI for Clinical Diagnostic Decision Making: Can Explainability be a Back-Stop Against Biased AI?

Friday February 2, 2024

Cornelius James, MD, UM

Specific Aims for the Equitable Prescribing and Access to Diabetes Technologies (ExPAnD Tech) Study

Friday January 19, 2024

Steven N. Hart, PhD, Mayo Clinic

A Deeper Dive into Large Language Models and their use in Pathology

Friday December 15, 2023

Michael Pencina, PhD, Vice Dean for Data Science, Duke University School of Medicine

& Matthew Elmore, ThD, AI Ethics and Evaluation Specialist, Duke University School of Medicine

The Coalition for Health AI (CHAI)”: Vision and Early Directions

Friday November 3, 2023

Brahmajee Nallamothu, MD, MPH & C. Alberto Figueroa, PhD,

A Data-driven Computational Framework for Assessing Epicardial and Microvascular Coronary Artery Disease using Angiography

Friday October 20, 2023

Emma Pierson, Assistant Professor of Computer Science at the Jacobs Technion-Cornell Institute

Using Machine Learning to Increase Equity in Healthcare and Public Health

Friday May 19, 2023

Marisa Conte, MLIS, Research Specialist Lead, Knowledge Systems Lab, Department of Learning Health Sciences, University of Michigan Medical School

FAIR (Findable, Accessible, Interoperable, Reusable) computational models can accelerate clinical research, improve care, and advance the goals of learning health systems

Friday May 5, 2023

Rohan Khera, MD, MS, Assistant Professor of Medicine and Biostatistics, Yale

Grant review

Friday April 21, 2023

Jean Feng, PhD, Assistant Professor, Department of Epidemiology and Biostatistics, University of California, San Francisco

Quality assurance and improvement for Machine Learning-based clinical decision support systems

Friday April 7, 2023, 2-3pm

John P. Donnelly, PhD, Department of Learning Health Sciences, U of M

& Sean Meyer, MBA, PhD, Lead Data Scientist, Precision Health Implementation Workgroup, U of M and HITS, Michigan Medicine

Precision Health Implementation: Introduction and Examples of Available Resources

Friday March 3, 2023

Karandeep Singh

Journal Club: Assessing the net benefit of machine learning models in the presence of resource constraints”

Friday February 17, 2023

Yanshan Wang, Ph.D., University of Pittsburgh

Clinical Natural Language Processing — How ChatGPT will fundamentally change the game

Friday January 20, 2023, 2-3pm

Zachi I Attia, PhD, Mayo Clinic

Developing AI models in a clinical environment- from an idea to a clinically used medical test

Friday January 6, 2023, 2-3pm

Eric Brandt, MD, MHS, FACC, Cardiovascular Medicine Division, U of M

Health Outcomes Related to Nutrition Policy – Measuring for Meaning

Friday December 16, 2022, 2-3pm

Maciej Mazurowski, PhD, Associate Professor in Radiology, Associate Professor in the Department of Electrical and Computer Engineering, Associate Professor in Biostatistics and Bioinformatics, Associate Professor of Computer Science, Member of the Duke Cancer Institute

How to find cancers without knowing what cancers look like

Location: Zoom | 12345

Friday November 4, 2022, 2-3pm

Rahul Ladhania, Assistant Professor, Departments of Health Management & Policy, Biostatistics, UM

Personalized Treatment Assignment Rules for Vaccine Uptake in Behavioral Science Field Experiments with Large Multi-Arm Trials

YouTube link

Friday October 21, 2022, 2-3pm

Ewout W. Steyerberg, PhD, Professor of Clinical Biostatistics and Medical Decision Making
Chair, Department of Biomedical Data Sciences, Leiden University Medical Center

Statistics and Machine Learning: friends or foes?

YouTube link

Friday October 7, 2022,

Yuri Zhukov, Assoc Prof, Ken Kollman, Fred G L Huetwell Prof, Ryan Rego, Impact Scholar/Rsrch Fellow, Ctr for Global Hlth Equity, UM

Promoting Data Harmonization to evaluate Vaccine Hesitancy in LMIC: Approach and Applications

YouTube link

Friday September 16, 2022

Esmee Venema, MD, MSc, Tufts Medical Center & Erasmus Medical Center

Personalized Reperfusion in Acute Ischemic Stroke

YouTube link

Friday May 20, 2022

Bobak Jack Mortazavi, Assistant Professor, PATHS-UP Engineering Research Center, Department of Computer Science & Engineering, Texas A&M University

Models to Enable Cuffless Blood Pressure Monitoring

YouTube link

Friday May 6, 2022

Journal Club led by Dr. Mike Sjoding

Diagnosis Physician Error: A Machine Learning Approach to Low-value Health Care

Friday April 15, 2022

David Ouyang, MD, Staff Physician, Smidt Heart Institute Department of Cardiology and Division of Artificial Intelligence in Medicine, Cedars Sinai Medical Center

Cardiovascular AI: Development to Deployment

YouTube link

Friday March 18, 2022

David Rushlow, M.D., Chair, Mayo Clinic Midwest Department of Family Medicine.

Tom D. Thacher, M.D. Vice-chair of Research, Mayo Clinic Midwest Department of Family Medicine.

Waking the Sleeping Giant – Engaging the Primary Care Practice in Pragmatic Trials

YouTube link

Friday March 4, 2022

Dr. Joel H. Rubenstein, Director, Barrett’s Esophagus Program and Professor, Division of Gastroenterology, University of Michigan Medical School Research Scientist, Veterans Affairs Center for Clinical Management Research

Using machine learning to adapt tools predicting esophageal adenocarcinoma for use with electronic medical data

Friday February 18, 2022

Dr. Che Ngufor, Assistant Professor of Biomedical Informatics, Mayo Clinic

Causal Machine Learning: Estimating Heterogeneous Treatment Effects with Observational Data

YouTube link

Friday February 4, 2022

Jessica Golbus, MD ~ Clinical Instructor in Cardiovascular Disease, UMs

Feedback Session on Specific Aims Page for K-Award

Friday January 21, 2022

Xiaoxi Yao, PhD MPH MS FACC FAHA, Mayo Clinic

Digital, Decentralized, and Pragmatic Clinical Trials: How to generate evidence at a fast pace and lower cost?

YouTube link

Friday January 7, 2022

Brahmajee Nallamothu, MD, MPH and Jessica Golbus, MD

Journal Club:”Megastudies Improve the Impact of Applied Behavioural Science” in Nature

December 17, 2021

Christine Gregg, Michael McManus, Park Szachta, and Jason Tan

Applying Natural Language Processing to Qualitative Research: Lessons Learned by MyVoice Student Researchers

December 3, 2021

Rohan Khera, MD, MS, Assistant Professor of Medicine, Section of Cardiovascular Medicine, Yale School of Medicine

Personalizing clinical trial interpretation through computational phenomaps

YouTube link

November 19, 2021

Barbara Barry, PhD., Assistant Professor, Division of Health Care Delivery Research / Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic.

Human–Artificial Intelligence (AI) Interaction: Supporting AI integration into Healthcare Systems

November 5, 2021

Neil Kamdar, MA, IHPI (Data & Methods Hub), U of M,

& Sarah Seelye, PhD, & Wyndy Wiitala, PhD, CCMR Ann Arbor VA

To Review or Not Review – Barriers and Facilitators to Code Review and Release

October 15, 2021

Armando Bedoya, MD, MMCi, Associate Chief Medical Informatics Officer, Associate Chair of Data Science, Department of Medicine, Duke University &

Benjamin A. Goldstein, PhD, Associate Professor, Department of Biostatistics & Bioinformatics, Duke Clinical Research Institute, Children’s Health & Discovery Initiative

Moderated by Dr. Michael Pencina

The ABCs of Predictive Model Governance

YouTube link

October 1, 2021

Jeremy Sussman, MD, MS Interviews Karandeep Singh, MD, MMSc.

Meet the Author

September 17, 2021

Big Data and AI in Health Seminar Series

Ricardo Henao, PhD, Assistant Professor in Biostatistics & Bioinformatics, Member of Duke Center for Applied Genomics and Precision Medicine, Member of the Duke Clinical Research Institute

Moderated by Michael Pencina, PhD, Vice Dean for Data Science & Information Technology, Professor of Biostatistics & Bioinformatics, Duke University School of Medicine

+Data Science: Data Science for Everyone

YouTube link

September 3, 2021

Zach Landis-Lewis PhD, Assistant Professor of Learning Health Sciences, U-M

Digital Health Interventions and Prediction Modeling

June 18, 2021

Andrew Vickers, PhD, Attending Research Methodologist, Department of Epidemiology & Biostatistics, Memorial Sloan Kettering Cancer Center, New York City, NY and Professor of Public Health, Weill Cornell Medical College, New York City, NY

David M. Kent MD, MS – Director, Predictive Analytics and Comparative Effectiveness Center, Tufts Medical Center

Moderated by Dr. Ewout Steyerberg, Prof of Clinical Biostatistics and Medical Decision Making, Leiden University Medical Center

How Do You Know Your Model is Not Harming Patients? The Case for Measures of Clinical Utility

June 4, 2021

Yi Li, Professor, Department of Biostatistics

Stephen Salerno, Yuming Sun, Emily Morris, Doctoral Students, Department of Biostatistics

A Comprehensive Evaluation of COVID-19 Patient Outcomes from an Early Hotspot After One Year: Risk Factors and Lessons Learned

May 21, 2021

David M. Kent MD, MS – Professor of Medicine, Neurology and Clinical and Translational Science from Tufts University

Understanding Covert and Cryptogenic Cerebrovascular Disease using Predictive Analytics: Research-in-Progress

May 7, 2021

Geoffrey H. Siwo, PhD, Assistant Research Professor, Center for Research Computing, & Eck Institute for Global Health, University of Notre Dame, IN, USA

Technologies for accelerating trustworthy, verifiable and auditable medical AI

April 16, 2021

Benjamin Wessler, MD, MS, Director of the Valve Center at Tufts Medical Center and Assistant Professor of Medicine and Clinical & Translational Science at Tufts University School of Medicine.

How Trustworthy are Cardiovascular Predictive Models.

April 2, 2021

Mohammed N. Islam PhD, Professor of Electrical & Computer Engineering and Biomedical Engineering, University of Michigan.

Contactless Physiological Measurements for Vital Sign Monitoring.

March 19, 2021

Jonathan D. Mosley MD, PhD, Assistant Professor of Medicine and Biomedical Informatics, Vanderbilt University Medical Center.

Genes and environment: I am the environment.

March 5, 2021

C. Alberto Figueroa PhD Edward B. Diethrich Professor of Surgery & Professor of Biomedical Engineering and

Kritika Iyer, Computational Vascular Biomechanics Lab, Biomedical Engineering, University of Michigan.

Algorithms and Challenges of Coronary Segmentation and Flow Extraction.

February 26, 2021

Rashmee U. Shah, MD, MS, Assistant Professor in Cardiovascular Medicine at the University of Utah School of Medicine

ICD, CPT, SNOMED, LOINC… WTF? The Art and Science of Healthcare Data

February 12, 2021

Jenna Wiens, PhD, Associate Professor, Division of Computer Science and Engineering.

Building out Reusable Precision Health Concepts for the Research Data Warehouse

January 29, 2021

Weijing Tang, Cheng Ma, Yang Li, & Xuefei Zhang, PhD & Ji Zhu, Prof and Associate Chair of the Department of Statistics

Association of University Reopening Policies with New Confirmed COVID-19 Cases in the United States

January 15, 2021

Jonny Sexton, PhD Assistant Professor in the Division of Gastroenterology and Hepatology and Medicinal Chemistry at U-M

Cell Painting: Single Cell Morphologic Profiling for Patient-Centric Drug Discovery/Repurposing.

December 18

Inbal (Billie) Nahum-Shani, PhD, Co-Director Data-Science for Dynamic Decision-Making Lab (d3lab), Institute for Social Research, U-M

Experimental Designs for Building mHealth Interventions: Connecting the Dots between Factorial Designs, SMARTs and MRTs

December 4, 2020

Karandeep Singh, MD, MMSc, Internal Medicine, Urology, and Information, U-M

R01: Predicting COVID Acute Kidney Injury Using Federated Machine Learning

November 20, 2020

Marzyeh Ghassemi, PhD, MSc, Asst. Prof of Computer Science and Medicine at the University of Toronto

Don’t Expl-AI-n Yourself: Exploring “Healthy” Models in Machine Learning for Health

November 6, 2020

Promo art with seminar series title, presenter, date, and time

Cooper Stansbury, MSc, Informatics PhD Student –U-M

Exploring Relationships Between the Michigan Built Environment and Our Health Through Aerial Imagery

October 23, 2020

David Kent, MD, CM, MS Prof of Medicine, Neurology and Translational Science, Tufts University &

Jessica Paulus, ScD, Investigator, Institute for Clinical Research and Health Studies, Tufts University

Predictably Unequal: Algorithmic Fairness and Bias in Healthcare

October 9, 2020

Nilay D Shah, PhD, Professor of Health Sciences Research at Mayo Clinic

Algorithms at the bedside: from model development to practice implementation

September 25, 2020

Joelle Pineau, PhD, MSc, BASc, Co-Managing Director at Facebook AI Research, Assoc Prof at McGill University & Faculty Member at Mila.

On the Development of Robust and Reproducible AI Systems for Automatically Learning Personalized Treatment Strategies

September 11, 2020

VG Vinod Vydiswaran, PhD, Asst Prof of Learning Health Sciences, Medical School & Asst Prof of Information, School of Information

Harnessing the Power of Clinical Text for Cohort Identification and Medication Extraction

May, 29, 2020

Alanson Sample, PhD, Associate Professor, Electrical Engineering & Computer Science

Sensing Systems for In-home Activity Inferencing and Health Monitoring

May 15, 2020

Rada Mihalcea, PhD, Professor, Electrical Engineering & Computer Science

The Artificial Intelligence Lab at Michigan: Ins and Outs ; Bonus: Natural Language Processing for Health Communication

March 6, 2020

Andrew Krumm, PhD, Associate Professor of Learning Health Sciences at U-M Medical School

Data-Intensive Approaches to Measuring Learning in Education and Health Systems: Reflections, Examples, and Implications

February 21, 2020

Karandeep Singh, MD, MMSc

Journal Club: A clinically applicable approach to continuous prediction of future acute kidney injury

February 7, 2020

James O. Woolliscroft, MD, MACP, FRCP, Professor of Internal Medicine and Learning Health Sciences

& Cornelius A. James, MD, Instructor of Internal Medicine and Pediatrics

Machine Learning meets Evidence-Based Medicine: A Users’ Guide for Clinicians

January 24, 2020

Saige Rutherford, BS, Data Analyst with MiSCAN Lab

The Current State of Prediction in Neuroimaging

January 10, 2020

Shengpu Tang, BSE, PhD student, Computer Science & Engineering, U-M

& Parmida Davarmanesh, College of Literature, Science, and the Arts student, U-M

Democratizing EHR Analyses – A Comprehensive, Generalizable Pipeline for Learning from Structured Clinical Data

December 20, 2019

Arvind Rao, Ph.D., Associate Professor, Dept of Computational Medicine & Bioinformatics and Radiation Oncology

& Tingyang Li, BS, Student

Bias and Fairness in Cardiovascular Disease Risk Prediction

December 6, 2019

Nicholson Price, JD, Asst Professor of Law, Michigan Law, U-M

Law, Innovation, and Bias in Medical AI

November 22, 2019

Hamid Ghanbari, MD

& Kevin Wheelock, Medical Student

Preliminary Results From the MiAfib Registry

November 8, 2019

Rajan Dewar, MBBS, PhD, Adjunct Associate Professor, Dept of Pathology, U-M

Maternal Health Worldwide – Is There a Role for Predictive Analytics to Improve Health Delivery?

October 25, 2019

Seth Klapman, BS, U-M MD/MBA Student
& Karandeep Singh, MD, MMSc, U-M Learning Health Sciences & Internal Medicine

1000 Heart Sounds: Leveraging Intelligent Auscultation to Predict Cardiovascular Disease

October 4, 2019

Michael Ho, MD, PhD, Professor of Medicine, University of Colorado School of Medicine and Co-Director of the Center for Innovation at Denver and Seattle VA Medical Centers

NavLab: Trials and tribulations of implementing a learning health system

September 27, 2019

Drew Bennett, MBA, U-M Office of Technology Transfer

Software Licensing 2020: IP Management – Open Source, Proprietary and Protection

September 13, 2019

Erin Kaleba, MPH, Data Office for Clinical and Translational Research
& Cinzia Smothers, M. Bioethics, U-M Precision Health

The Precision Health Analytics Platform: Data, Analytics, and Resources for Your Research

June 20, 2019

Rahul Deo, MD, PhD, One Brave Idea

Doing more with less … extending cardiovascular diagnostic interpretation beyond human ability

May 31, 2019

Hae Mi Choe, PharmD, Associate Dean for Pharmacy Innovations and Clinical Associate Professor, College of Pharmacy, U-M
& Amy Pasternak, PharmD, Clinical Assistant Professor of Pharmacy and Clinical Pharmacist, College of Pharmacy, U-M

Precision Health Implementation at Michigan Medicine

May 17, 2019

Karandeep Singh, MD, MMSc,Assistant Professor in Learning Health Sciences and Internal Medicine U-M

Potential FDA Regulation of Artificial Intelligence/Machine Learning Algorithms

April 19, 2019

Danai Koutra, PhD, Assistant Professor, Computer Science & Engineering, U-M

Fast Inference and Mining of Functional Brain Networks

March 22, 2019

Nikola Banovic, PhD, Assistant Professor, Electrical Engineering & Computer Science, U-M

A Computational Modeling Approach to Predicting Hospital Readmission

March 8, 2019

Hamid Ghanbari MD, MPH, Cardiologist, Assistant Professer, U-M

Novel Techniques for Evaluation of Symptoms in Atrial Fibrillation: A Machine Learning Approach

February 22, 2019

Laura Balzano, PhD,Assistant Professor in Electrical Engineering and Computer Science,U-M

Finding Low-rank Structure in Messy Data

February 14, 2019

MIDAS Music Challenge recipient:

Somangshu Mukherji, PhD, Assistant Professor of Music Theory, U-M

Computational Music Theory and Music as the “Universal Language”

February 8, 2019

Tim Guetterman, PhD, Assistant Professor, Co-Director, Michigan Mixed Methods Program, U-M
& Vinod Vydiswaran, PhD, Assistant Professor of Learning Health Sciences, Medical School and Assistant Professor of Information, School of Information, U-M

Natural Language Processing/Machine Learning for Qualitative Data Review and Analysis

January 25, 2019

Richard Gonzalez, PhD, Amos N. Tversky Collegiate Professor of Psychology and Statistics, U-M

You Say `Features’, I Say `Variables’ – Exploring Key Differences between Statistical and Machine Learning Approaches to Modeling Data

January 11, 2019

MIDAS Health Science Challenge recipients:

Anna Gilbert, PhD, Herman Goldstine Collegiate Professor, Dept of Mathematics, U-M
& Jun Li, PhD, Professor & Associate Chair for Research of Computational Medicine and Bioinformatics, U-M

An Overview of the MIDAS Single Cell Data Analysis Center: Analysis, Modeling, and Applications

December 7, 2018

Ben Wellner, PhD, MITRE Corporation

Predicting Septic Shock in Pediatric Intensive Care Units (PICUs)

November 9, 2018

Karthik Duraisamy, PhD, Michigan Engineering, Michigan Institute for Computational Discovery and Engineering (MICDE)

Machine Learning Augmented Predictive Modeling of Complex Systems

November 8, 2018

Donald Likosky, PhD, Associate Professor, Dept of Cardiac Surgery, U-M
& Steven Yule, PhD, Associate Professor of Surgery, Harvard Medical School

Novel Assessments of Technical and Non-Technical Cardiac Surgery Quality

November 2, 2018

Mike Sjoding, MD, Pulmonary and Critical Care Medicine, Internal Medicine, U-M
& Jenna Wiens, PhD, Computer Science and Engineering, U-M

Using Reinforcement Learning to Identify Optimal Treatment Policies for Acute Respiratory Failure

October 19, 2018

Jodyn Platt, MPH, PhD, Assistant Professor of Learning Health Sciences

Introducing Predictive Models into the Clinical Space: Designing Trustworthy Systems

October 12, 2018

Ulysses Balis, MD, Professor of Pathology, U-M Medical School

Early Insights from the Application of Machine Vision and Machine Learning Techniques to Histopathological Subject Matter

August 10, 2018

Vincent Liu, MD, MSc, Kaiser Permanente Northern California Division of Research

Towards Precision Delivery: Balancing Prediction and Phenotyping

June 1, 2018

Elliott Brannon, MPH (MD/PhD student) & Karandeep Singh, MD, MMSc

Towards a Learning Health System to Reduce Emergency Department Visits at a Population Level

May 18, 2018

Mohammed Saeed, MD, PhD

Creating Healthcare Databases to Support Research in Machine Learning: Lessons Learnt from MIMIC

May 11, 2018

Donald Likosky, PhD & Michael Mathis, MD

Development and Evaluation of Novel Computer-Assisted Assessments of Technical and Non-technical Cardiac Surgery Quality

May  4, 2018  – MiCHAMP / CHOP / IHPI Combined Event

David Hodgson, MD, MPH,  University of Toronto

Change has its Enemies: Opportunities and Barriers in the Adoption of Machine Learning Methods in Oncology


Danielle Rodin, MD, MPH, University of Toronto

Variation in Cancer Spending: Implications for Value-Based Care

See the MiCHAMP News Post

April 18 to April 20, 2018

John P.A. Ioannidis, MD, DSc, Stanford University

• The Power of Bias and What to do About it
• Precision Health, Big Data and Evidence-Based Medicine—Contradictions or Companions?
View this seminar
• Reproducible and Useful Clinical Research: Mission Impossible?

For more information, see the MiCHAMP News

April 6, 2018

Jiaxuan Wang, BS, Ian Fox, & Jenna Wiens, PhD

The Advantage of Doubling: A Deep Reinforcement Learning Approach to Studying the Double Team in the NBA

March 23, 2018

Kayvan Najarian, PhD

Major Challenges of Using AI in Healthcare and Potential Solutions

March 9, 2018

Dr. Steffen Leonhardt, MD, PhD, Professor, RWTH Aachen University, Aachen, Germany.

Thou Shalt Not Touch – Nonobtrusive and Noncontact Monitoring Techniques for Medical Applications

*this lecture was co-sponsored by MiCHAMP, MCIRCC, and U-M Department of Computational Medicine & Bioinformatics

February 9, 2018

Andrew Gelman, PhD, Professor of statistics and political science and Director of the Applied Statistics Center at Columbia University.

What’s Wrong with ‘Evidence-Based Medicine’ and How Can We Do Better?

*this seminar was co-sponsored by MiCHAMP, Interdisciplinary Statistical Learning Workshop (LSA Political Science) & the Department of Philosophy

January 26, 2018

Jeff McCullough, PhD

Causal Inference in Machine Learning with Applications for Heterogeneous Treatment Effects for Medical Device Utilization

January 12, 2018

Hallie Prescott, MD, MSc

Upcoming IIR on Hospital Performance Measurement

January 10, 2018

Mohammad Ghassemi

Healthcare 2.0: Integrating Health and Behavioral Data for AI-driven Care


December 15, 2017

Seth Klapman and Karandeep Singh, MD, MMSc

Digital Auscultation to Predict Echo Findings in Cardiovascular Disease

December 8, 2017

Wenshou Liu, PhD

Journal Club – Deep Learning

November 17, 2017

Yun Jiang, PhD, MS, RN

Mobile Sensor Data-to-Knowledge (MD2K) – NIH Training Institute 2017 Scholar

November 3, 2017

Akbar Waljee, MD, MSc, Ji Zhu, PhD, MSc, Xuefei Zhang, BS, Boang Liu, MA, and Tony Van

Predicting Hep C Progression Using Machine Learning

October 19, 2017

John Spertus, MD, MPH, FACC, CCMR Distinguished Visiting Professor; Director, Health Outcomes Research, Saint Luke’s Mid American Heart Institute; Professor, University of Missouri-Kansas City.

The Past, Present and Future of Patient-Reported Outcomes

October 6, 2017

Tim Guetterman, PhD

Bioinformatics and Education

September 22, 2017

Tejas Prahlad, Dan Zeiberg, and Mike Sjoding, MD

Data-Driven Patient Risk Stratification for Acute Respiratory Distress Syndrome

September 8, 2017

Brahmajee Nallamothu, MD, MPH

Internal Medicine Bicentennial Presentation

May 19, 2017

James Davies

We Predict, and a Health Use Case

May 12, 2017

Mike Mathis, MD

Integrating Perioperative Care into the Diagnosis of Heart Failure: A Data Science Approach

May 5, 2017

Ravi Shah and Venk Murthy, MD, PhD

Integrated Cardiovascular Phenotyping and Molecular Characterization: From Populations to Molecules

April 28, 2017

Matt Churpek, MD, MPH, PhD

Using EHR Data to Detect Clinical Deterioration

April 21, 2017

Jack Iwashyna, MD, PhD

ResCU II – “Long-Term Trajectories of Recovery Following Serious Hospitalization with In-Hospital Cardiac Arrest”

March 10, 2017

Ryan Stidham, MD & Akbar Waljee, MD, MSc

Big Data / Better Data: Using Machine Vision in Crohn’s Disease

February 17, 2017

Srijan Sen, MD, PhD

Medical Internship as a Model to Identify Real-Time Objective Predictors of Depression under Stress

January 27, 2017

Ian Fox and Jenna Wiens, PhD

Contextual Motifs – Improving the Utility of Motifs for Analyzing Physiological Signals

January 20, 2017

Mike Sjoding, MD and Kayvan Najarian, PhD

New Machine-learning Paradigms to Improve Identification of Acute Respiratory Distress Syndrome

January 13, 2017

Anna Kratz, PhD

God is in the Details: Ambulatory Methods and Mysteries of Health-related Quality of Life

January 6, 2017

Adam Markovitz, MD, PhD, Mike Mathis, MD,  Jeremy Sussman, MD, MS

SPRINT Challenge Update – 3 Approaches and a Discussion

December 16, 2016

Sardar Ansari, PhD and Kayvan Najarian, PhD

Polyvinylidene Fluoride Based Sensor for Non-invasive Hemodynamic Monitoring

December 9, 2016

Venkatesh Murthy, MD, PhD

Molecular Markers of Early Cardiometabolic Health Transitions

December 2, 2016

Andy Ryan, PhD and Jeff McCullough, PhD

Nowcasting & Forecasting Health Expenditures

November 11, 2016

Allen Flynn, PharmD

Digital Library of Learning (Computable Knowledge Object Library System)

October 28, 2016

Karandeep Singh, MD, MMSc

Using Clinical Notes to Uncover Everyday Natural Experiments in Healthcare

October 21, 2016

Jeremy Sussman, MD, MS

Improving Doctors’ Report Card with Analytics:  Benefit-Based Performance Measurement in Cardiovascular Disease

October 7, 2016

Jacob Mack, MD, BS

SPRINT Challenge