Seminar Series on Quantitative Medicine
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The Seminar Series on Quantitative Medicine will resume in October 2013. Please join our mailing list to stay updated on new speakers and events. 

Past Speakers


DATE (Monday, 2013) 


January 28



February 4



February 11



February 25 



March 4




March 11



March 18



March 25



April 1



April 8



April 29



May 6



May 20




SPEAKER


Dr. Julie Silver
(Harvard Medical School)

link to bio

Dr. Alan Geller
(Harvard School of Public Health)

link to bio

Dr.  Griffin Weber 
(Harvard Medical School,
BIDMC Biomedical Research Informatics Core)

link to bio

Dr. Richard Frank 
(Harvard Medical School) 

link to bio

Dr. Shawn Murphy
(Lab of Computer Science,

Harvard Medical School)
link to bio

Dr. John Gilbertson 
(MGH Pathology Informatics) 
link to bio

Dr. Robert Huckman 
(Harvard Business School) 

link to bio

Amit Kulkarni
(Informatics-IT, Merck and Co.)
link to bio

Ariel Stern 
(Harvard Kennedy School)

link to bio

Dr. Sandra Lee
(Harvard School of Public Health, 
Dana-Farber Cancer Institute)

link to bio

Dr. Cynthia Rudin
(MIT Sloan School of Management,
Prediction Analysis Laboratory) 

link to bio

Dr. Anita Tucker 
(Harvard Business School) 

link to bio

Dr. Mary Beth Landrum
(Harvard Medical School)
link to bio


TOPIC


Cancer Rehabilitation: 
The Next Frontier in Survivorship Care


The German Skin Cancer Screening Experience: Methods and First Results


Analyzing Collaboration Using Harvard Catalyst Profiles: Quantitative methods of analyzing network data (description)

Enrollment in Medicare Advantage: 
An Accident of Birth


Instrumenting the Health Care Enterprise for Discovery Research: innovative use of electronic healthcare data in developing and performing clinical trials & genomic research

The Rise of Pathology Informatics and Evolution of Laboratory Information System (LIS): What's wrong and is there any hope of fixing it

Healthcare's Humpty Dumpty Challenge: Specialization in the Era of Accountable Care (description)

Merck's Crowdsourcing Efforts on Predictive Modeling Problems: a pilot with Kaggle (description) 

Physician Beliefs and Patient Preferences: a New Look at Regional Variation in Spending


Models for Early Detection of Chronic Diseases: Applications to Breast Cancer Screening

Interpretable Machine Learning Algorithms and Their Applications to Heathcare


Fostering Organizational Learning:  The Impact of Work Blockages on Workarounds, Errors, and Speaking Up about Internal Supply Chain Problems

Use of Geographic Variation to Infer Treatment Effectiveness: A Cautionary Tale
description


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