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TZID:Europe/London
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BEGIN:VEVENT
UID:109@oxon.bcs.org
DTSTART;TZID=Europe/London:20261202T183000
DTEND;TZID=Europe/London:20261202T210000
DTSTAMP:20261113T193422Z
URL:https://oxon.bcs.org/programme/genome-detectives-what-ai-can-and-cant-
 tell-us-in-the-fight-against-infection/
SUMMARY:Genome Detectives: What AI Can and Can't Tell Us in the Fight Again
 st Infection
DESCRIPTION:\nProfessor Daniel Wilson\, MA\, DPhil\nProfessor of Infectious
  Disease Genomics\nArtificial intelligence promises to transform medicine\
 , but in the fight against infection\, being able to predict something is 
 not the same as understanding it. In this talk\, Danny Wilson shows how ma
 chine learning and traditional statistics each help "genome detectives" re
 ad bacterial DNA: tracing food poisoning back to its source\, uncovering w
 hy bugs we carry harmlessly sometimes turn deadly\, and predicting which a
 ntibiotics will still work. Along the way he asks what AI can and can't te
 ll us\, why the best predictions aren't always the best answers\, and why 
 there is cause for hope against bacterial infections that claim millions o
 f lives each year.\n\n\n\nDanny Wilson is Professor of Infectious Disease 
 Genomics at the University of Oxford. He is Director of Studies in Data Sc
 ience at Oxford Lifelong Learning\, based at Rewley House\, and a Fellow o
 f St Cross College. He leads a research group at the Big Data Institute\, 
 part of Oxford Population Health\, where his research combines data scienc
 e\, statistics and genomics to understand where bacterial infections come 
 from\, why they cause disease\, who is most at risk\, and how resistance t
 o antibiotics arises. He works with the Modernising Medical Microbiology a
 nd leads Bugbank\, a project linking microbiology data to UK Biobank and O
 ur Future Health.\nAgenda\n18:30 - In person Reception\n19:00 - Branch Ann
 ouncements and Special Guests\n19:30 - Christmas Lecture
ATTACH;FMTTYPE=image/jpeg:https://oxon.bcs.org/wp-content/uploads/2026/11/
 header-genome-virus-thumb.jpg
CATEGORIES:Hybrid Event
LOCATION:Rewley House\, 1 Wellington Square\, Oxford\, Oxfordshire\, OX1 2J
 A\, United Kingdom
X-APPLE-STRUCTURED-LOCATION;VALUE=URI;X-ADDRESS=1 Wellington Square\, Oxfor
 d\, Oxfordshire\, OX1 2JA\, United Kingdom;X-APPLE-RADIUS=100;X-TITLE=Rewl
 ey House:geo:0,0
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DTSTART:20261025T010000
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