Events Add an event Speakers Talks Collections
 
Duration 03:06
16+
Video

C8 Predicting antibiotic resistance in Mycobacterium tuberculosis with genomic machine learning

Chang Ho Yoon
PhD Research Fellow at Big Data Institute
+ 6 speakers
  • Video
  • Table of contents
  • Video
Machine Learning for Healthcare
August 8, 2020, Online, Los Angeles, CA, USA
Machine Learning for Healthcare
Request Q&A
Machine Learning for Healthcare
From the conference
Machine Learning for Healthcare
Request Q&A
Video
C8 Predicting antibiotic resistance in Mycobacterium tuberculosis with genomic machine learning
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Add to favorites
476
I like 0
I dislike 0
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
  • Description
  • Transcript
  • Discussion

About the talk

00:00 Intro

00:25 Slow diagnosis

00:52 Whole-genome sequences + ML

01:27 CNN Architecture

01:57 Deep CNN = WDNN

02:07 CNN: we can check the predictions

02:43 A promising diagnostic + research tool

About speakers

Chang Ho Yoon
PhD Research Fellow at Big Data Institute
Anna Green
Research Fellow in Biomedical Informatics at Harvard Medical School Department of Biomedical Informatics
Michael Zhu Chen
Intern, Life Sciences Investment Team at Oxford Sciences Innovation
Luca Freschi
Postdoctoral Research Fellow at Harvard Medical School
Isaac Kohane
Professor & Chair, Department of Biomedical Informatics at Harvard Medical School
Andrew Beam
Assistant Professor of Biomedical Informatics at Harvard Medical School
Maha Farhat
Assistant Professor of Biomedical Informatics at Harvard Medical School

Chang Ho Yoon’s training in internal medicine has taken him from London to Auckland. His interest in the application of computer technology in clinical practice spurred him to lead the development and research of a smartphone app for antibiotic guidelines at an academic hospital. As a Fulbright Scholar, BEST Scholar, and a Gavin & Ann Kellaway Medical Research Fellow, he hopes to study machine learning and large-scale data integration during the master’s program in order to segue into a PhD. Dr. Yoon's research interests include machine learning, data science, smartphone healthcare apps, cancer genomics, epidemic prediction, and technology in medical education.

View the profile

Anna Green is a computational biologist who loves to think about the evolution of bacterial genomes. She did her PhD in Debora Mark's lab, where she studied the evolution and specificity of protein interactions, and developed methods to detect interactions from genomic sequences. Anna is working to integrate techniques for phenotype prediction for protein and genome sequences, and applying these methods to understand the evolution and pathology of Mycobacterium tuberculosis.

View the profile

A bioinformatician who fell in love with evolutionary biology. He enjoys using cutting-edge computational tools to study how microbial genomes work and evolve. Further, he loves to teach! He joined the Farhat lab in 2017 and he is currently studying the role of insertions and deletions on the evolution and pathogenicity of Mycobacterium tuberculosis.

View the profile

Andrew Beam is an assistant professor in the Department of Epidemiology at the Harvard T.H. Chan School of Public Health, with secondary appointments in the Department of Biomedical Informatics at Harvard Medical School and the Department of Newborn Medicine at Brigham and Women’s Hospital. His research develops and applies machine-learning methods to extract meaningful insights from clinical and biological datasets, and he is the recipient of a Pioneer Award from the Robert Wood Johnson Foundation for his work on medical artificial intelligence. Previously he was a Senior Fellow at Flagship Pioneering and the founding head of machine learning at Generate Biosciences, Inc., a Flagship-backed venture that seeks to use machine learning to improve our ability to engineer proteins. He earned his PhD in 2014 from N.C. State University for work on Bayesian neural networks, and he holds degrees in computer science (BS), computer engineering (BS), electrical engineering (BS), and statistics (MS), also from N.C. State. He completed a postdoctoral fellowship in Biomedical Informatics at Harvard Medical School and then served as a junior faculty member.

View the profile

Maha Farhat holds an MD from the McGill University Faculty of Medicine and a MSc in biostatistics from the Harvard Chan School of Public Health. She is also a practicing physician at the Massachusetts General Hospital Division of Pulmonary and Critical Care Medicine. Dr. Farhat’s research focuses on the development and application of methods for associating genotype and phenotype in infectious disease pathogens, with a strong emphasis on translation to better diagnostics and surveillance in resource-poor settings. To date, Farhat’s work has focused on the pathogen Mycobacterium tuberculosis and spans the spectrum from computational analysis to field studies. She is PI and Co-Investigator on several large projects funded by NIH including the NIAID and the BD2K initiative.

View the profile
Share
Cackle comments for the website

Buy this talk

Access to the talk “C8 Predicting antibiotic resistance in Mycobacterium tuberculosis with genomic machine learning”
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free

Ticket

Get access to all videos “Machine Learning for Healthcare”
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Ticket

Interested in topic “Artificial Intelligence and Machine Learning”?

You might be interested in videos from this event

February 4 - 5, 2021
Online
26
147
ai, application, bot, chatbot, conversation, data, design, healthcare, ml

Similar talks

Besmira Nushi
Principal Researcher at Microsoft
+ 1 speaker
Byron Wallace
Associate Professor at Northeastern University
+ 1 speaker
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Emma Brunskill
Assistant professor of computer science at Stanford University
+ 1 speaker
Finale Doshi-Velez
Gordon McKay Professor in Computer Science at Harvard University
+ 1 speaker
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
George Cortina
PhD at Duke University
+ 11 speakers
Shujin Zhong
Data Analyst Intern at Duke Institute for Health Innovation
+ 11 speakers
Marshall Nichols
Senior IT & Analytics Manager at Duke Institute for Health Innovation
+ 11 speakers
Michael Gao
Data Science Lead at Duke Institute for Health Innovation
+ 11 speakers
William Ratliff
Innovation Program Manager at Duke University Health System
+ 11 speakers
Will Knechtle
ДолжностьInnovation Program Manager, Duke Institute for Health Innovation at Duke University Health System
+ 11 speakers
Suresh Balu
Program Director at Duke School of Medicine
+ 11 speakers
Mary Lindsay
Registered nurse at Duke University
+ 11 speakers
Jill Engel
Associate Vice President - Heart Operations, Nursing & Patient Care Services at Duke University Health System
+ 11 speakers
Ricardo Henao
Assistant Professor in Biostatistics and Bioinformatics at Duke University
+ 11 speakers
Mark Sendak
Population Health & Data Science Lead at Duke Institute for Health Innovation
+ 11 speakers
Mihai Podgoreanu
Anesthesiologist, Critical Care Specialist at Duke University
+ 11 speakers
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free

Buy this video

Video
Access to the talk “C8 Predicting antibiotic resistance in Mycobacterium tuberculosis with genomic machine learning”
Available
In cart
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free
Free

Conference Cast

With ConferenceCast.tv, you get access to our library of the world's best conference talks.

Conference Cast
946 conferences
37592 speakers
14370 hours of content
Chang Ho Yoon
Anna Green
Michael Zhu Chen
Luca Freschi
Isaac Kohane
Andrew Beam
Maha Farhat