Thursday September 19th 20198 - Hammersmith Campus

"Machine Learning for Translational Medicine & Personalized Healthcare"

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About

This worskhop is organized by the ITMAT Data Science Group of the NIHR Imperial Biomerdical Research Centre (BRC). It will gather Imperial College speakers to discuss current challenges and opportunities in using data science for translational medicine.

Location:  Lecture Theatre 1,  Wolfson Centre, Imperial College Hammersmith Campus, London W12 0NN

Programme

9h30:10h00
Welcome  Coffee & Tea

10h00:11h00 - METABOLOMICS

 

1. Prof. Jules Griffin, Dpt. Metabolism-Digestion-Reproduction, Faculty of Medicine - “Challenges of performing metabolomics and lipidomics at the population level” (20')

2. Dr. Andrea Rodriguez-Martinez, School of Public Health, Faculty of Medicine - “Overview of the MWASTools R/bioconductor package for metabolome-wide association studies” (10')

3. Dr. Marc Dumas, Dpt. Metabolism-Digestion-Reproduction, Faculty of Medicine- “Convergence between metabolomics, genomics and metagenomics” (20')

4. Wrap up (10')

 

11h00:11h30 - POPULATION HEALTHCARE

           

1. Prof. Mauricio Barahona, Dpt of Mathematics, Faculty of Natural Sciences - “ML for Precision Healthcare” (20')

2. Dr. Sam Greenbury, ITMAT Data Science Group, NIHR Imperial Biomedical Research Centre - “MALNEO BRC project: Machine Learning on the Neonatal Registry” (10')

 

11h30:12h00 - TEACHING DATA SCIENCE WITHIN THE FACULTY OF MEDICINE

           

1. Dr. Tim Ebbels, Dpt. Metabolism-Digestion-Reproduction, Faculty of Medicine - “Data Science Stream in the Biomedical Research MRes” (10')

2. Dr. Matt Williams, Dpt. of Surgery and Cancer, Faculty of Medicine & Dpt. of Computing, Faculty of Engineering – “Teaching Coding to medicine undergraduate students” (10')

3. Discussion (10')

12h00-13h00: Lunch Break

 
 

13h00:13h30 - BRAINSTORMING PANNEL SESSION: "HOW TO BETTER BUILD SYNERGIES AROUND DATA SCIENCE AND MACHINE LEARNING FOR MEDICINE"

 

 
 

13h30:14h30 - MEDICAL IMAGING

 

1. Dr. Ben Glocker, Dpt. of Computing, Faculty of Engineering - “Spot-the-Lesion: Image- based disease detection with deep learning” (20')

2. Tim Hoogenboom, Dpt. Metabolism-Digestion-Reproduction, Faculty of Medicine – “MALLUS BRC project: Deep Learning on liver ultrasound for multi-disease classification” (10')

3. Dr. Louise Paterson, Dpt. of Brain Sciences, Faculty of Medicine – “ADOBE BRC project: Machine Learning on brain imaging for prediction of relapse & patient stratification in an addiction cohort” (10')

4. Dr. Bill Crum, ITMAT Data Science Group, NIHR Imperial Biomedical Research Centre / Prof. Andrea Rockall, Dpt. of Surgery and Cancer, Faculty of Medicine / Prof. Eric Aboagye, Dpt. of Surgery and Cancer, Faculty of Medicine – “Populating a clinical imaging research database: governance and technical challenges” (10')

5. Wrap Up (10')