Past Seminars at the ITA

June 14, 2022

Dr. Soroush Saghafian, PhD – Can Public Reporting Cure Healthcare?

Mar 15, 2022

Constance “Connie” Lehman, MD, PhD – Deep learning and breast cancer: AI for good

Feb 8, 2022

Dr. Hawre Jalal, MD PhD – Prominent spatiotemporal patterns of COVID-19 case incidence in the US

Nov 9, 2021

Dan Ollendorf, PhD – It’s the Prices, Stupid: Evolution of Health Technology Assessment in the U.S. and Impact on Pricing

Sept 14, 2021

Pinar Keskinocak, PhD – Modeling Infectious Diseases: Projecting Spread, Evaluating Interventions, and Resource Allocation

May 11, 2021

Ashish A. Deshmukh, PhD, MPH – Changing trajectories of HPV-associated cancers and opportunities for control

April 20, 2021

Elizabeth Burnside, MD, MPH, MS – Precision Breast Cancer Screening: An Iterative Learning Health System Intervention

March 9, 2021

Jeremy D. Goldhaber-Fiebert, PhD – COVID-19 Policy Modeling and Links to Decision Makers

January 19, 2021

Benjamin Linas, MD MPH – Simulation modeling to improve the care of opioid use disorder in the U.S

December 15, 2020

David Kim, PhD, MS – Perspective in Cost-Effectiveness Analysis: 2nd US Panel’s Deliberations and Practical Guidelines for Analysts

November 24, 2020

Ankur Pandya, PhD – A framework for responding to health-improving but cost-ineffective health care

October 20, 2020

Sana Raoof, MD, PhD – American Oncology: Our history, unmet needs, and future opportunities

September 8, 2020

Madeline Adee, MPH – Ignoring the incarcerated: how people in jails and prisons are excluded from health statistics and health services, and the impact this has on disease modeling

May 12, 2020

Jennifer M. Yeh, PhD – Early initiation of breast cancer screening in childhood cancer survivors: Insights from a collaborative modeling study

April 14, 2020

Davene R. Wright, PhD – Goldilocks and the three disciplines: crafting an interdisciplinary research agenda to improve child health

February 18, 2020

Sandra J. Lee, PhD – Collaborative Modeling for Breast Cancer Screening

January 14, 2020

Danielle Currie, PhD – Falling for the wrong ‘solution’?

December 10, 2019

Nikhil Panda, MD – Building the Digital Phenotype of Recovery after Surgery: Harnessing Smartphone Data to Improve Quality of Life Assessment

November 19, 2019

TA Trikalinos, MD, PhD – lation of computationally expensive mathematical models

October 15, 2019

Marc Larochelle, MD, MPH – Using “big data” to respond to the crisis of opioid-related harms

September 18, 2019

Sung Eun Choi, PhD – Cost-effectiveness of treating oral disease among patients with type II diabetes

May 28, 2019

Kerry Reynolds, MD – Immunotherapy: More Questions than Answers

April 9, 2019

Jamie Cohen, MPH – TBD

March 12, 2019

Ryan Nipp, MD, MPH Patient-Reported Physical and Psychological Symptom Burden among Hospitalized Patients with Cancer

February 12, 2019

Steven Lubitz, MD MPH – Atrial Fibrillation: to Screen or Not to Screen

January 2019

Laura Brattain, PhD – Machine Learning for Translational Medicine

December 2018

Florian Fintelmann, MD – Role of Body Composition Metrics in Lung Cancer Care

October 2018

Frank Wharam, MD MPH – High-deductible Insurance and Cancer Care: Early Efforts to Quantify Toxicity

February 2018

Anthony Samir, MD MPH – Ultrasound as a Quantitative Imaging Biosensor: Emerging Applications and Opportunities with a focus on Synthetic Liver Biomarkers

December 2017

Selin Merdan, PhD candidate – Predictive Analytics for Optimal Detection of Metastatic Prostate Cancer

November 2017

Sarah Mercaldo, PhD – Strategies to deal with missing predictor values when constructing, validating, and applying clinical prediction models

Nate Mercaldo, PhD – Efficient study designs for longitudinal binary data

October 2017

Vicki Fung, PhD – Opioid use among patients with serious mental illness

September 2017

Krishna Reddy, MD – Tobacco and HIV: Model-based Approaches to Study Converging Epidemics

August 2017

Kelvin Tsoi, PhD – Classification of Visit-to-Visit Blood Pressure Variability: A Machine Learning Approach for Data Clustering on Systolic Blood Pressure Intervention Trial (SPRINT)