Upcoming Events

Precisely Practicing Medicine from 700 Trillion Points of Data

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. 

Lawrence Lessig, JD

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

Lawrence Lessig is the Roy L. Furman Professor of Law and Leadership at Harvard Law School. Prior to returning to Harvard, he taught at Stanford Law School, where he founded the Center for Internet and Society, and at the University of Chicago. He clerked for Judge Richard Posner on the 7th Circuit Court of Appeals and Justice Antonin Scalia on the United States Supreme Court.Lessig is the founder of Equal Citizens and a founding board member of Creative Commons, and serves on the Scientific Board of AXA Research Fund. A member of the American Academy of Arts and Sciences and the American Philosophical Society, he has received numerous awards including a Webby, the Free Software Foundation's Freedom Award, Scientific American 50 Award, and Fastcase 50 Award Cited by The New Yorker as “the most important thinker on intellectual property in the Internet era,” Lessig has focused much of his career on law and technology, especially as it affects copyright. His current work addresses “institutional corruption”—relationships which, while legal, weaken public trust in an institution—especially as that affects democracy. 

People, Ideas, and Machines

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.

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

Prospects for Hyper-Personalized Medicine

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

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

BCH AI and Machine Learning Journal Club

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

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

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

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.

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