Upcoming Events

Landmark Ideas Series: Dr. Rich Miner

Speaker: Rich Miner, PhD, Android Co-founder; Co-founder at GV

Date: January 12, 2023 at 4:00PM - 5:30PM

Dr. Mandl and Dr. Miner will have a fireside chat.

Landmark Ideas Series: Prof. Allan Brandt

Speaker: Allan Brandt, PhD, Leading Historian of Medicine and Science. University Professor at Harvard University

Date: February 9, 2023 at 4:00PM - 5:30PM

Talk details will be forthcoming.

Landmark Ideas Series: Dr. Julie Gerberding

Speaker: Julie Gerberding, MD, MPH, CEO at Foundation for the National Institutes of Health, Former Director, CDC

Date: April 3, 2023 at 4:00PM - 5:30PM

Talk details will be forthcoming.

Landmark Ideas Series: Karen Copenhaver

Speaker: Karen Copenhaver, Legal Counsel at The Linux Foundation

Date: May 1, 2023 at 4:00PM - 5:30PM

Talk Topic: Using Licensing to Maximize Innovation in The Open Source Software Ecosystem.

Landmark Ideas Series: Dr. Robert Langer

Speaker: Robert Langer, ScD, Institute Professor at MIT; most cited engineer in history

Date: September 7, 2023 at 4:00PM - 5:30PM

Talk details will be forthcoming.

Landmark Ideas Series: Dr. W. Ian Lipkin

Speaker: W. Ian Lipkin, MD, Renowned virus hunter and Director for the Center of Infection and Immunity at Columbia University

Date: October 5, 2023 at 4:00PM - 5:30PM

Talk details will be forthcoming.

Landmark Ideas Series: Dr. Thom Mayer

Speaker: Thom Mayer, MD, FACEP, FAAP, FACHE, Medical Director at NFL Players Association

Date: December 7, 2023 at 4:00PM - 5:30PM

Talk details will be forthcoming.

Landmark Ideas Series: Dr. Mollyann Brodie

Speaker: Mollyann Brodie, PhD, Director of Public Opinion and Survey Research Program at the Kaiser Family Foundation

Date: January 29, 2024 at 4:00PM - 5:30PM

Talk details will be forthcoming.

Landmark Ideas Series: Dr. Toby Cosgrove

Speaker: Toby Cosgrove, MD, Former CEO and current Executive Advisor at the Cleveland Clinic

Date: February 12, 2024 at 4:00PM - 5:30PM

Talk details will be forthcoming.

Previous Events

Chip 25th Anniversary Symposium

Separating the Signal from the Noise: Establishing the Foundation for Healthcare in 2044
Harvard Club

Date: October 20, 2019

The Boston Children’s Hospital Computational Health Informatics Program celebrated our 25th Anniversary last year with a Symposium “Separating the Signal from the Noise: Establishing the Foundation for Healthcare in 2044” at the Harvard Club of Boston.

Landmark Ideas Series

Landmark Ideas Series: Ray Kurzweil

Speaker: Ray Kurzweil, Inventor and Futurist at Google and Kurzweil AI

Date: December 5, 2022 at 4:00PM - 5:00PM

Talk Topic: Rewriting Biology with Artificial Intelligence.

Intelligent Health Lab Series: Dr. Nathan Kuppermann

Speaker: Nate Kuppermann, MD, MPH, Distinguished Professor, Departments of Emergency Medicine and Pediatrics; Associate Dean for Global Health at University of California, Davis School of Medicine

Date: October 20, 2022 at 4:00PM - 5:00PM

Talk Topic: How a large a collaborative research network reshapes evidence generation for pediatric care.

Landmark Ideas Series: Mihaela van der Schaar

Speaker: Mihaela van der Schaar, The John Humphrey Plummer Professor of Machine Learning, AI, and Medicine at the University of Cambridge

Date: October 3, 2022 at 4:00PM - 5:30PM

Talk Topic: Machine Learning and Revolutionizing Healthcare.

Landmark Ideas Series: Dr. Derrick Rossi (Video Available)

Speaker: Derrick Rossi, PhD, Co-founder at Moderna

Date: September 19, 2022 at 4:00PM - 5:30PM

Talk Topic: Stem Cell Science and the Genesis of New Therapeutic Strategies for Patients.

Intelligent Health Lab Series: Dr. Dave Ferrucci

Speaker: Dave Ferrucci, PhD, Founding Lead PI of IBM Watson (Former); CEO at Elemental Cognition

Date: September 12, 2022 at 4:00PM - 5:00PM

Talk Topic: The Tale of Two AI's - From Vision to Market.

Landmark Ideas Series: Dr. Vinay Prasad (Video Available)

Speaker: Vinay Prasad, MD, MPH, American Hematologist-Oncologist and Health Researcher, Associate Professor at the University of California, San Francisco

Date: May 5, 2022 at 4:00PM - 5:30PM

Talk Topic: Medical Reversal: Why 46% of What Doctors Think Is Wrong In this lecture we will talk about the rate with which medical practices are widely adopted and later found to be lacking. We will explore some of the causes and solutions. 

Landmark Ideas Series: Dr. Rob Knight (Video Available)

Speaker: Rob Knight, PhD, Co-founder at The American Gut Project

Date: March 17, 2022 at 4:00PM - 5:30PM

Talk Topic: Linking Human and Environmental Microbiomes for Health.

Landmark Ideas Series: Dr. Todd Golub (Video Available)

Speaker: Todd Golub, MD, Director of the Broad Institute at MIT and Harvard

Date: February 17, 2022 at 4:00PM - 5:30PM

Genomic Approaches to Cancer Precision Medicine Dr. Golub will present findings from his laboratory and the Broad Institute Cancer Program utilizing large-scale pre-clinical models for therapeutic target discovery and approaches to cancer precision medicine. 

Landmark Ideas Series: Envisioning Clinical Evidence Generation of the Future (Video Available)

Speaker: Amy Abernethy, MD, PhD; Former Principal Deputy Commissioner and acting Chief Information Officer of Food and Drugs of the US Food and Drug Administration (FDA), President of Clinical Studies Platforms at Verily

Date: January 20, 2022 at 4:00PM - 5:30PM

Clinical research is undergoing a major shift, as regulators and sponsors move towards continuous evidence generation to study how interventions perform over time. In this talk, we’ll explore what’s accelerating this trend, how new tools and technologies are advancing the space, and how it can ultimately enable more personalized care.

Searching for the Origin of Covid-19 (Video Available)

Speaker: Alina Chan, Molecular Biologist at the Broad Institute at MIT and Harvard University

Date: November 15, 2021 at 4:00PM - 5:30PM

In May 2020, I co-authored a preprint that asked whether SARS-CoV-2 might have emerged naturally or from a lab. The preprint propelled me into an unpredictable year-and-a-half journey of searching for the origin of Covid-19. In May 2021, I agreed to write down what I had learnt in a book that will be released on November 16, VIRAL: The Search for the Origin of Covid-19. In this Landmark talk, I will discuss the role of scientists in the investigation of how SARS-CoV-2 emerged in Wuhan in late 2019. I will also describe the available data relevant to the origin of Covid-19, and how scientists can and must play an important role in what is possibly the most important mystery of our generation. This virus will be with us forever. We need to know where it came from.

Water Quality and Child Survival (Video Available)

Speaker: Michael Kremer, PhD, 2019 Nobel Laureate, Director of the Development Innovation Lab, University Professor in Economics and the College and the Harris School of Public Policy at the University of Chicago

Date: November 4, 2021 at 4:00PM - 5:30PM

The Computational Future and Biomedicine (Video Available)

Speaker: Stephen Wolfram, PhD, Founder and CEO at Wolfram Research

Date: October 7, 2021 at 4:00PM - 5:30PM

Dr. Stephen Wolfram  –  creator of Mathematica, Wolfram|Alpha and the Wolfram Language; the author of A New Kind of Science; the originator of the Wolfram Physics Project; and the founder and CEO of Wolfram Research – will speak about the computational future and biomedicine. Dr. Wolfram will share a roadmap for recentering biomedicine around computation and give insights into harnessing data driven science to transform the biomedical landscape. This should be a relevant and an illuminating talk from one of the foremost leaders in computational health.  

People, Ideas, and Machines (Video Available)

Speaker: Enrico Coiera, PhD, Director of the Centre for Health Informatics at Australian Institute of Health Innovation

Date: April 29, 2021 at 5:00PM - 6:30PM

In an age where technology appears to rule supreme, it is easy to forget that our relationship with technology is complicated. Just as humans shape technology, it shapes us in return. It is also easy to only see things through the lens of the technologies we have to hand, and build solutions that ill fit reality. Electronic health records for example demand that clinical work bends to the needs of documentation, with the end result being burnt out clinicians who do anything but what they were taught at medical school. Algorithms built with our cleverest machine learning methods just end up making concrete the biases implicit in their data sets. Seeing human systems like healthcare as sociotechnical systems helps us understand these unintended consequences, and gives us a different lens to understand technology design and use.

The Privacy Confusion First Thoughts on Clearer Thinking (Video Available)

Speaker: Lawrence Lessig, JD, Founder of Creative Commons, Roy L. Furman Professor of Law and Leadership at Harvard Law School

Date: March 1, 2021 at 4:00PM - 5:30PM

Privacy has become a central focus of policy debates in every context. In this talk, Lessig argues that we’re conceiving of the problem in a fundamentally flawed way. Offered is a different framework, radically different but critically better. Or so it is hoped.

Precisely Practicing Medicine from 700 Trillion Points of Data (Video Available)

Speaker: Atul Butte, MD, PhD, Priscilla Chan and Mark Zuckerberg Distinguished Professor at UCSF and Chief Data Science Officer at University of California Health System

Date: February 22, 2021 at 4:00PM - 5:30PM

There is an urgent need to take what we have learned in our new data-driven era of medicine, and use it to create a new system of precision medicine, delivering the best, safest, cost-effective preventative or therapeutic intervention at the right time, for the right patients.  Dr. Butte's lab at the University of California, San Francisco builds and applies tools that convert trillions of points of molecular, clinical, and epidemiological data -- measured by researchers and clinicians over the past decade and now commonly termed “big data” -- into diagnostics, therapeutics, and new insights into disease.  Dr. Butte, a computer scientist and pediatrician, will highlight his center’s recent work on integrating electronic health records data across the entire University of California, and how analytics on this “real world data” can lead to new evidence for drug efficacy, new savings from better medication choices, and new methods to teach intelligence – real and artificial – to more precisely practice medicine. 

Prospects for Hyper-Personalized Medicine (Video Available)

Speaker: Timothy Yu, MD, PhD, Neurogeneticist and Researcher at Boston Children's Hospital

Date: January 11, 2021 at 4:00PM - 5:30PM

Genome sequencing is revolutionizing the diagnosis of rare diseases, but 95% of these conditions still lack effective therapy. With up to 7,000 distinct genetic diseases to tackle, new and creative frameworks will be necessary to meet this need. Recent advances offer the prospect of platform-based therapeutic approaches to certain genetically targetable disorders — in the right circumstances, facilitating the design and deployment of hyper-personalized drugs for conditions affecting as few as even a single patient. The scientific, clinical, ethical, and regulatory implications of these capabilities will be discussed.

Event Horizon Telescope: Imaging a Black Hole Through Global Collaboration (Video Available)

Speaker: Shep Doeleman, PhD, 2020 Breakthrough Prize Winner; Astrophysicist at Center for Astrophysics

Date: November 9, 2020 at 4:00PM - 5:30PM

What can medicine learn about collaboration and data sharing from one of the most successful team science projects of all time--creating a telescope the diameter of the earth to snap an image of a black hole? Black holes are cosmic objects so massive and dense that their gravity forms an event horizon: a region of spacetime from which nothing, not even light, can escape. Einstein's theories predict that a distant observer should see a ring of light encircling the black hole, which forms when radiation emitted by infalling hot gas is lensed by the extreme gravity. The Event Horizon Telescope (EHT) is a global array of radio dishes that forms an Earth-sized virtual telescope, which can resolve the nearest supermassive black holes where this ring feature may be measured. On April 10th, 2019, the EHT project reported success: we have imaged a black hole and have seen the predicted strong gravitational lensing that confirms the theory of General Relativity at the boundary of a black hole.  This talk will describe the project, and the global collaborative approach that produced these first results, as well as future directions that will enable real-time black hole movies.

Interoperability at Scale
Landmark Center at 401 Park Drive, 5th floor East, Boston, MA 02215

Speaker: Ricky Bloomfield, MD, Clinical and Health Informatics Lead at Apple

Date: March 2, 2020 at 4:00 PM - 5:30 PM

Healthcare has been slow to adopt scalable, interoperable, user-centric solutions as other industries have done, but technology is finally catching up with the needs of patients. Ricky will share how Apple's support and use of open standards has helped accelerate adoption across the country.

Forces Shaping the Future of the Internet
Landmark Center at 401 Park Drive, 5th floor East, Boston, MA 02215

Speaker: David Clark, PhD, MS, An Inventor of the Internet; Technical Director at MIT Internet Policy Research Initiative

Date: February 13, 2020 at 4:00PM - 5:30PM

In the early days of the Internet, technical innovation shaped its future. Today, issues of economics, market dynamics, incentives, and some fundamental aspects of networked systems shape the future. This talk will summarize eleven forces that are shaping the future of the Internet and make an argument that we are at a point of inflection in the character of the Internet, as profound as the change in the 1990’s when the Internet was commercialized.

Social Network Interventions
Landmark Center at 401 Park Drive, 5th floor East, Boston, MA 02215

Speaker: Nicholas A. Christakis, MD, PhD, MPH, Scientist and Physician at Yale University

Date: December 16, 2019 at 4:00PM - 5:30PM

Human beings choose their friends, and often their neighbors and co-workers, and they inherit their relatives; and each of the people to whom we are connected also does the same, such that, in the end, we humans assemble ourselves into face-to-face social networks. Why do we do this? How has natural selection shaped us in this regard? What role do our genes play in the topology of our social ties? And how might a deep understanding of human social network structure and function be used to intervene in the world to make it better?

Big Tech and the National Health Service: Maintaining Equity in the AI Revolution
Where: Landmark Center at 401 Park Drive, 5th floor East, Boston, MA 02215

Speaker: Maxine Mackintosh, PhD, Winston Churchill Fellow at the Alan Turing Institute and University College London

Date: October 21, 2019 at 4:00PM - 5:30PM

A day does not go by without a new framework for ethics in AI, particularly in health and social care. But when your health system is based on need versus ability to pay, yet the skills, computational power and often data lies in tech companies, from SMEs to multinationals, it can be difficult to see how a health system can digitize in an equitable and ethical manner. Maxine’s talk will share some examples of the learnings, attitudes and practical ways the UK has approached data stewardship, partnerships, “intangible assets" and transparency of health data organizations looking to work with the NHS. These examples will include learnings from DeepMind Health’s Independent Review Board, the use of consumer data in the UK for health research, and how the UK is approaching some of these discussions at a national, policy level.

BCH AI and Machine Learning Working Group

Leveraging ML for Fetal Acquisition and Analysis

Speaker: Ellen Grant, MD, Director, Fetal-Neonatal Neuroimaging and Developmental Science Center; Borjan Gagoski, PhD, Faculty MR Physician, Fetal-Neonatal Neuroimaging and Developmental Science Center; Junshen Xu, PhD, Student, at MIT

Date: February 11, 2022 at 9:30AM - 10:30AM

Fetal magnetic resonance imaging is challenging to perform as the fetus continually moves during image acquisition. As a result, the technologist must know how to "chase the fetus" to get images orthogonal to the fetal brain and repeat these acquisitions until images without motion are obtained. In this talk we will discuss how ML approaches are being used to accelerate and automate fetal imaging acquisition. Fetal imaging can be a challenge, but fetal motion also provides insight into the neurological and musculoskeletal development of the fetus. We will also describe how we have used ML approaches to track and quantify fetal motion and the potential neuroscientific and clinical applications.

BCH AI and Machine Learning Working Group Journal Club

Speaker: Ben Reis, PhD and Ilkin Bayramli, at Boston Children's Hospital

Date: February 1, 2022 at 2:00PM - 3:00PM

Dr. Ben Reis and Ilkin Bayramli will present their paper in Journal of the American Medical Informatics Association (JAMIA) entitled "Temporally informed random forests for suicide risk prediction": -https://pubmed.ncbi.nlm.nih.gov/34725687/

Fireside Chat At Decision Points in Clinical Pathways

Speaker: Drs. Arjun Manrai, Amy Starmer, and Robert Rosen, at Boston Children's Hospital

Date: January 21, 2022 at 09:30AM - 10:30AM

A discussion among Drs. Arjun Manrai, Amy Starmer, and Robert Rosen, moderated by Dr. Ken Mandl.

BCH AI and Machine Learning Working Group Journal Club

Speaker: Byron Wallace, PhD, Associate Professor at Northeastern University

Date: December 14, 2021 at 2:00PM - 3:00PM

Dr. Wallace will talk about their work in text summarization and simplification, and issues related to factual accuracy of generated texts: - https://arxiv.org/abs/2104.05767- https://arxiv.org/abs/2008.11293

BCH AI and Machine Learning Working Group Journal Club

Speaker: Alal Eran, PhD, Faculty, Computational Health Informatics Program at Boston Children's Hospital

Date: November 30, 2021 at 2:00PM - 3:00PM

Dr. Eran presented her paper in Nature Medicine entitled "A multidimensional precision medicine approach identifies an autism subtype characterized by dyslipidemia": https://www.nature.com/articles/s41591-020-1007-0.

Contemporary Symbolic Regression Methods for Interpretable Machine Learning

Speaker: William La Cava, PhD, Faculty, Computational Health Informatics Program at Boston Children's Hospital

Date: September 17, 2021 at 09:30AM - 10:30AM

Most interpretable machine learning research focuses on explaining the outputs of black-box models. A different, and promising, approach is to use machine learning to find the simplest possible model that meets certain performance criteria; this is the pursuit of symbolic regression. In this talk I will discuss the concepts of interpretability and explainability, and how they are used in the machine learning world. I will then discuss a pre-print that will be published in the Neurips Datasets and Benchmarks track later this year. In it, we attempt to benchmark many different approaches to symbolic regression on hundreds of problems in order to determine the strengths and weaknesses of current methods. I will discuss what lies ahead and implications for how clinicians and patients receive and process models that increasingly appear in the health system.   This event is only open to Boston Children's staff. If you would like to attend the Zoom details, please email CHIP@childrens.harvard.edu. 

Valid Inference After Hierarchical Clustering

Speaker: Lucy Gao, PhD, Assistant Professor of Statistics at the University of Waterloo

Date: May 11, 2021 at 2:00PM - 3:00PM

Dr. Gao will discuss the following article: Gao, Bien, and Witten (2020). Selective inference for hierarchical clustering. arXic:2012.02936. This journal club is only available to the BCH community. If you would like to be sent a calendar invite please email chip@childrens.harvard.edu. 

BCH AI and Machine Learning Journal Club: Andrew Beam, PhD

Speaker: Andrew Beam, PhD, Assistant Professor, Department of Epidemiology at the Harvard T.H. Chan School of Public Health

Date: April 13, 2021 at 2:00PM - 3:00PM

Dr. Beam led a discussion on the following article: Tom B Brown, Benjamin Mann, Nick Ryder, et al. Language models are few-shot learners. arXiv preprint arXiv:2005.14165 [cs], 2020. Dr. Beam also discussed results from his group that evaluates this model on medical applications. 

Real-world COVID-19 Vaccine Effectiveness and the Mass Vaccination Experience in Israel

Speaker: Ben Reis, PhD, Director, Predictive Medicine Group, Computational Health Informatics Program (CHIP), Faculty at at Harvard Medical School

Date: March 16, 2021 at 2:00PM - 3:00PM

Dr. Ben Reis will lead a discussion on the recent New England Journal of Medicine paper he co-authored, providing the first real-world study of effectiveness of the Pfizer-BioNTech COVID-19 vaccine. It was the largest study yet to quantify the impact of the vaccine outside the confines of a clinical trial. The study used innovative epidemiological methods to analyze vaccine effectiveness for preventing symptomatic diseases, severe illness and death. Dr. Reis will discuss his study and the lessons learned from the nation-wide mass vaccination experience in Israel. The study has been featured in The New York Times, Bloomberg, and Fortune.

BCH AI and Machine Learning Working Group Journal Club James Diao

Speaker: James Diao, MD, Harvard Medical School MD Student at Boston Children's Hospital

Date: February 23, 2021 at 2:00PM - 3:00PM

James will lead a discussion on approaches to addressing racial equity concerns with clinical algorithms, including for arthritis severity (Pierson et al. 2021) and kidney function estimates (Diao et al. 2021):

Let us get practical: developing and disseminating AI research and workflows to audiences of researchers and clinicians within BCH using the ChRIS platform

Speaker: Rudolph Pienaar, PhD, Staff Scientist at Boston Children's Hospital

Date: January 29, 2021 at 09:30AM - 10:30AM

We are often wowed by the *potential* of AI (and frankly other sophisticated computational approaches) to transform research and clinical workflows. New approaches seem to magically hold unbounded promise. Yet, there is often a large gulf between theory and practice, between a shiny new technique and having anyone just use it. The questions of "How do I get this ? How do I get my data from PACS to connect to this? How do I go from DICOM to something that the neural network wants? How do I get results that are useful?" In this talk I will provide some insights into practically developing, using, and disseminating "AI" (and other) workflows in the BCH clinical and research environment.

BCH AI and Machine Learning Journal Club: Guergana Savova, PhD

Speaker: Guergana Savova, PhD, Associate Professor of Pediatrics, Computational Health Informatics Program at Boston Children's Hospital

Date: December 8, 2020 at 4:45PM - 5:30PM

Dr. Savova led a discussion of tasks and applications of clinical Natural Language Processing (NLP) in medicine, such as: The landscape of neural approaches and clinical NLP (Wu et al, 2019; https://pubmed.ncbi.nlm.nih.gov/31794016/) Data challenges in clinical NLP (de-identified data, usability and challenges) Some tasks and applications Information extraction for cancer surveillance (DeepPhe-CR) (Savova et al, 2017; https://pubmed.ncbi.nlm.nih.gov/29092954/) Treatment information extraction (Bitterman et al, 2020 https://www.aclweb.org/anthology/2020.clinicalnlp-1.21.pdf; Lin et al, 2020 https://www.aclweb.org/anthology/2020.louhi-1.12.pdf) What is trending.

BCH AI and Machine Learning Journal Club: Danielle Rasooly, PhD

Speaker: Danielle Rasooly, PhD, Postdoctoral Fellow, Computational Health Informatics Program at Boston Children's Hospital

Date: November 10, 2020 at 4:45PM - 5:30PM

Dr. Rasooly led a discussion of the following paper about Google/DeepMind's AI system for breast cancer screening: McKinney et al. International evaluation of an AI system for breast cancer screening. Nature2020. as well as the following paper AI transparency/reproducibility: Haibe-Kains et al. Transparency and reproducibility in artificial intelligence. Nature 2020. ​The two papers are accessible as pdfs here.

The Age of Predictive Medicine

Speaker: Ben Reis, PhD, Faculty, Computational Health Informatics Program (CHIP); Director, Predictive Medicine Group, Computational Health Informatics Program (CHIP) Assistant Professor of Pediatrics, Harvard Medical School at Boston Children's Hospital

Date: October 16, 2020 at 09:30AM - 10:30AM

Dr. Ben Reis discussed recent developments in machine learning approaches to some of the grandest challenges of human health, including pandemic prediction, suicide prevention, bioterrorism detection, and drug safety prediction. The focus was on understanding both the methodological challenges involved and the ramifications of generating actionable predictions in these critical areas. The talk concluded by formulating a set of central challenges and opportunities facing the field of Predictive Medicine.

BCH AI and Machine Learning Working Group Lightning Talks

Date: September 9, 2020 at 09:30AM - 10:30AM

The BCH AI and Machine Learning Working Group held our first Lightning Talks session, where multiple investigators gave brief overviews of numerous Machine Learning applications at Boston Children’s Hospital to foster clinical and machine learning collaborations across the hospital.

A Gold Mine of Potential: Predictive Analytics Using Boston Children’s Hospital’s “Children’s 360” Data Warehouse

Speaker: Jonathan Bickel, MD, MS; Ronald Wilkinson, MA, MS, CBIP; Ashley Doherty, MS, at

Date: August 14, 2020 at 09:30AM - 10:30AM

Boston Children’s Hospital data warehouse integrates 15 years of extensive clinical and administrative data sources and more years of selected data sources. While the contents are used extensively for daily operational reporting, the potential for extensive retrospective and predictive analytics is largely untapped. Jonathan Bickel, Ashley Doherty, and Ron Wilkinson will show something of the breadth of data available in the EDW, discuss how predictive modeling tools can access the data, discuss ideas for predictive modeling applications that they think would be valuable, and explain the conditions on which access to the data can be granted.

AI in 3D Medical Images: Concepts, Milestones, and Opportunities

Speaker: Yangming Ou, PhD, Assistant Professor of Radiology; Affiliate Faculty, Computational Health Informatics Program; Faculty, Fetal-Neonatal Neuroimaging Data Science Center at Boston Children's Hospital

Date: July 17, 2020 at 09:30AM - 10:30AM

Dr. Yangming Ou briefly reviewed some major concepts and milestones of AI in medical images. The focus of Dr. Ou’s talk was on 3D medical images, for AI’s application in disease diagnosis, outcome prediction, early screening, neuroscience, and others. Dr. Ou then discussed some major challenges and potential opportunities, including further improving accuracy in detecting small diffuse lesions, and facilitating AI in small sample sizes.

BCH AI and Machine Learning Journal Club: Tim Miller, PhD

Speaker: Tim Miller, PhD, Assistant Professor of Pediatrics, Computational Health Informatics Program at Boston Children's Hospital

Date: June 30, 2020 at 4:45PM - 5:30PM

Dr. Timothy Miller discussed articles that he recently published on natural language processing of computerized text. 1. Dligach D, Majid A, Miller T. Toward a Clinical Text Encoder: Pretraining for Clinical Natural Language Processing With Applications to Substance Misuse. SSRN. 2020. 2. Miller T, Avillach P, Mandl K. Experiences Implementing Scalable, Containerized, Cloud-based NLP for Extracting Biobank Participant Phenotypes at Scale. SSRN. 2020.

BCH AI and Machine Learning Journal Club: Arjun Manrai, PhD

Speaker: Arjun (Raj) Manrai, PhD, Faculty, Computational Health Informatics Program (CHIP); Director, Laboratory for Probabilistic Medical Reasoning; Assistant Professor, Harvard Medical School at Boston Children's Hospital

Date: May 8, 2020 at 09:30AM - 10:30AM

Blood laboratory measures such as glucose and hemoglobin are the basis for much of clinical decision making, yet baseline variation for many laboratory measures remains incompletely characterized across age, gender, and race groups. I will introduce foundational techniques from machine learning and statistical genetics and show how they can be applied to systematically unpack variation in blood laboratory data across population groups. These analyses reveal widespread demographic structure in blood laboratory data.

Frontline Dispatch Series

Intelligent Health Lab Series: Dr. Sebastian Schneeweiss

Speaker: Sebastian Schneeweiss, MD, ScD, Pharmacoepidemiologist, Professor at Harvard Medical School

Date: November 21, 2022 at 4:00PM - 5:00PM

Talk Title: Real-world evidence for a learning healthcare system: moving from claims data to claims with linked EHR data.

Frontline Dispatch Series: Dr. Wanda Barfield

Speaker: Wanda Barfield, MD, MPH, FAAP, RADM USPHS (ret.), Director, Division of Reproductive Health at Centers for Disease Control (CDC)

Date: November 10, 2022 at 4:00PM - 5:00PM

Talk Title: Maternal and Infant Health Data Equity and Modernization: Are We There Yet?

CHIP Frontline Dispatch Series: Dr. Christopher Longhurst

Speaker: Christopher Longhurst, MD, Chief Medical Officer and Chief Digital Officer at UC San Diego Health

Date: April 4, 2022 at 4:00PM - 5:00PM

Talk Topic: Interoperable Pandemic IT Innovations in California at Population Scale.

Frontline Dispatch Series: Accelerated Drug Approval and Aducanumab

Speaker: Aaron Kesselheim, MD, JD, MPH, Professor of Medicine at Harvard Medical School

Date: September 23, 2021 at 4:00PM - 5:30PM

Dr. Aaron Kesselheim, former member of the FDA’s Peripheral and Central Nervous System Drugs Advisory Committee who resigned over the agency’s approval of Aducanumab, will speak about the FDA’s accelerated approval pathway, how it is implemented, and how it was applied in the controversial Aducanumab case – which he dubbed the “worst drug approval decision in recent U.S. history.” Dr. Kesselheim will also give suggestions for the future. This should be a fascinating talk with wide implications for all future accelerated drug approval pathways.

Dispatch from Israel: COVID-19 Vaccines and the Delta Variant: What we know so far

Speaker: Ben Reis, PhD, Assistant Professor of Pediatrics, Computational Health Informatics Program at Boston Children's Hospital

Date: July 22, 2021 at 3:00PM - 4:00PM

The Delta (B.1.617.2) variant of the SARS-CoV-2 virus has rapidly emerged as the dominant strain spreading in many countries worldwide. Dr. Ben Reis led a discussion reviewing the latest findings on the Delta variant, with a focus on the effectiveness of approved COVID-19 vaccines against this emerging viral strain. Dr. Reis reviewed the evidence available from scientific publications, preliminary studies and public health reports, in the context of the inherent challenges involved in real-world vaccination effectiveness studies. He discussed the lessons learned from the nation-wide mass-vaccination experience in Israel and other highly vaccinated countries such as the UK, and provided an update on how these countries are responding dynamically to the threats posed by this emerging variant.