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Soroush Saghafian's work: Cutting ER Lines via Tele-Triage
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Soroush Saghafian's work: Improving Qualtiy Transparency in Healthcare [National Academy of Medicine]
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Soroush Saghafian's work: Increasing Transparency in the Healthcare System May Not Be Always Better [www.news-medical.net]
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Soroush Saghafian's work: Increasing Transparency in the Healthcare Sector: More Might Not Be Bette [INFORMS]
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Soroush Saghafian's work: New Research Explores on Increasing Transparency in the Healthcare Sector [Industry Global News 24]
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Soroush Saghafian's work: Increasing Transparency in the Healthcare Sector: More Might Not Be Bette [Global Health News Wire]
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Soroush Saghafian's work: Increasing Transparency in the Healthcare Sector: More Might Not Be Bette [EurekAlert; American Association for the Advancement of Science]
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Soroush Saghafian's work: Increasing Transparency in the Healthcare Sector: More Might Not Be Bette [Managed Healthcare Executives]
- Soroush Saghafian's research paper received POMS (Production and Operations Management Society) 2019 College of Healthcare Best Paper Award (first place)
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Soroush Saghafian has been awarded by National Science Foundation (NSF) to study new data-driven ways for medication management (Award Abstract)
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Soroush Saghafian's research paper received INFORMS Public Secotr Best Paper Award (second place)
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Soroush Saghafian's research paper received INFORMS MSOM (Manufacturing & Service Operations Management) Journal 2016 Best Paper Award (awarded to one paper among all published in the prior three years)
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Soroush Saghafian's research paper received INFORMS MSOM Society 2016 Best Paper Award of Service Special Interest Group (SIG)
Soroush Saghafian
Assistant Professor of Public Policy (Management, Leadership, and Decision Making), Harvard Kennedy School, Harvard University
79 JFK Street,
Cambridge, MA 02138
Soroush Saghafian on Twitter
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Detailed mathematical modeling and high-fidelity simulations would have provided great insights and could have saved $$$$$. Using observational data alone and/or waiting many years for an RCT is not always the right choice. I wish more people realize this. t.co/GIGjWCqpfL
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News coverage of our recent study. Increasing #transparency in the #healthcare system may not be always better t.co/mIp49qF5Yx
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Congratulations to winners of our #MachineLearning #competition. Winners among many students from @Harvard @MIT @TuftsUniversity @harvard_data @Kennedy_School @HarvardChanSPH @HarvardHBS @hgse: @Uzairistan, @kapilecon, Victor Sheng, Rose Burnam, Tasha Blaskovich, & Emma Davis.
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Thank you @Cardiology for spreading the result of our study. t.co/W0LXqjY279
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CCing some colleagues who might find this NAM paper interesting and might have good thoughts/comments @amitabhchandra2 @Cutler_econ @ashishkjha @robert_huckman t.co/dbtYxEnTly
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Quality transparency plays an important role in the healthcare sector. Our latest work, published by the National Academy of Medicine, discusses the related challenges and solutions. t.co/exeaPqT70w
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@KayseMaass @Northeastern @Harvard Thanks, Kayse! I very much enjoyed the visit.
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Giving large-scale talks with an interpreter is not that easy. But looking forward to talking at @harvard_law school and discussing with #Chinese #executives how and why their #business #strategy needs to be modified in the era of #MachineLearning & #ArtificialIntelligence
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Thank you for sharing. CC @sclaudwhitehead @KHNews t.co/KVYn9JKvbJ
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Had a great semester w fantastic students curious a/b the range of possibilities #MachineLearning #Analytics and #AI offer for solving societal problems. Hope they NEVER stop being a student @Harvard @Kennedy_School @harvard_data . And sorry @PomsSociety for missing #POMS2019 t.co/DCACuJeVrc
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@harvard_data t.co/cEE9NtQ2xM
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Congratulations to the three talented MS and PhD students from @Harvard and @MIT who won our #MachineLearning competition this semester: Utsav Sohoni (3rd), Gabriel Walker (2nd), Yu Qian Ang (1st). Fantastic performance! Well-deserved!
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@yudapearl @JoshuaSGoodman @oziadias Your seven tools of CI paper provides a very useful summary for students. I also introduced #Bookofwhy so that students that are interested can dig deeper. Both of these are also assigned in my full semester #MachineLearning class. Important for students to be exposed, IMO.
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Enjoyed teaching #MachineLearing to #econometric PhD students. Essential for them to know some of the newer techniques. Also, glad I got the chance to discuss @yudapearl views of #CausalInference with them. Thankful to my colleagues @JoshuaSGoodman and @oziadias .
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Interested to learn about a generalization of #Bayesian method? See the Second Order Belief Maximum Entropy (#SOBME) method in: t.co/SOPQdJhEOR #orms #MachineLearning #Statistics #BayesianLearning #AI #DecisionMaking
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Can’t wait until I submit my first paper to a journal with a fully #AI and #MachineLearning based review system. Human judgement is biased, algorithms are not. Just don’t train them on human-based data (which is automatically biased) and you’ll be fine. Learn from #AlphaGoZero.
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Nice piece by @Priyanka_Dayal. But we also need quality transparency and public reporting on outcomes. Can’t ignore quality and focus on prices. t.co/oSm8kTMYMs t.co/jiIsuW05VN via @BostonGlobe