BEGIN:VCALENDAR VERSION:2.0 PRODID:-//UC Irvine//CML Seminars//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:From Models to Medicine: Theoretical Foundations and Practical Impact of Machine Learning in Healthcare X-WR-TIMEZONE:America/Los_Angeles BEGIN:VTIMEZONE TZID:America/Los_Angeles BEGIN:DAYLIGHT TZOFFSETFROM:-0800 TZOFFSETTO:-0700 TZNAME:PDT DTSTART:20070311T020000 RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU END:DAYLIGHT BEGIN:STANDARD TZOFFSETFROM:-0700 TZOFFSETTO:-0800 TZNAME:PST DTSTART:20071104T020000 RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:2025-08-07-julia-vogt@cml.ics.uci.edu DTSTAMP:20250807T000000Z SEQUENCE:57690 DTSTART;TZID=America/Los_Angeles:20250807T130000 DTEND;TZID=America/Los_Angeles:20250807T140000 SUMMARY:[CML Seminar] Julia Vogt: From Models to Medicine: Theoretical Foun dations and Practical Impact of Machine Learning in Healthcare LOCATION:Donald Bren Hall 4011 DESCRIPTION:Julia Vogt\, Assistant Professor\, Department of Computer Scien ce\, ETH Zurich\n\nTitle: From Models to Medicine: Theoretical Foundations and Practical Impact of Machine Learning in Healthcare\n\nAbstract: The f usion of artificial intelligence and medicine is driving a healthcare tran sformation\, enabling personalized treatment tailored to each patient's un ique needs. By leveraging advances in machine learning\, we can transform challenging and diverse patient data into actionable insights that have th e potential to reshape clinical practice. In this presentation\, I will co ver both the theoretical foundations and practical applications of machine learning in healthcare. I will highlight innovative approaches designed t o enhance diagnostics\, improve patient care\, and make medical decision-m aking more accessible and reliable. I will touch on five fundamental\, int erconnected areas: multimodal data integration\, unsupervised structure de tection\, longitudinal data analysis\, transparent model development\, and development of decision support tools. Through real-world medical example s\, I aim to illuminate the collaborative future of machine learning and h ealthcare.\n\nhttps://cml.ics.uci.edu/seminars/2025-08-07-julia-vogt X-ALT-DESC;FMTTYPE=text/html:Julia Vogt\, Assistant Prof essor\, Department of Computer Science\, ETH Zurich

Title: F rom Models to Medicine: Theoretical Foundations and Practical Impact of Ma chine Learning in Healthcare

Abstract: The fusion of artific ial intelligence and medicine is driving a healthcare transformation\, ena bling personalized treatment tailored to each patient's unique needs. By l everaging advances in machine learning\, we can transform challenging and diverse patient data into actionable insights that have the potential to r eshape clinical practice. In this presentation\, I will cover both the the oretical foundations and practical applications of machine learning in hea lthcare. I will highlight innovative approaches designed to enhance diagno stics\, improve patient care\, and make medical decision-making more acces sible and reliable. I will touch on five fundamental\, interconnected area s: multimodal data integration\, unsupervised structure detection\, longit udinal data analysis\, transparent model development\, and development of decision support tools. Through real-world medical examples\, I aim to ill uminate the collaborative future of machine learning and healthcare.
https:/ /cml.ics.uci.edu/seminars/2025-08-07-julia-vogt URL:https://cml.ics.uci.edu/seminars/2025-08-07-julia-vogt END:VEVENT END:VCALENDAR