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DTSTART:20231105T020000
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UID:calendar.3097.events_uoft_date.0@www.statistics.utoronto.ca
CREATED:20240311T145223Z
DESCRIPTION:\nWhen and Where: \nMonday, April 29, 2024 3:30 pm to 4:30 pm
  \n Room 306 \n Leonard G. Lumbers Building (LUM), York University \n 115
  Ottawa Road, Toronto, ON \n\nSpeakers \nLarissa Stanberry \n\nDescripti
 on: \nMedical field is abuzz with artificial intelligence, that is disrup
 ting health care by transforming its many aspects from image analysis and 
 drug discoveries to patient monitoring, to healthcare operations and publ
 ic health initiatives. In clinical research, this impact is felt through 
 the steady increase in the number of clinical prediction models, proclaim
 ing novel predictors and promising superior accuracy, intuitive use, and
  drastic improvements in patient outcomes and resource allocation. This in
 crease is due not only to growing availability of healthcare data and deve
 lopments in analysis methodology, but also, and in no small part, to ad
 vances in modern software lowering the barriers to entry. The democratizat
 ion of technology and the advancement of user-friendly tools are allowing 
 researchers with varying skill sets to try their luck in developing clinic
 al prediction models.We conducted a systematic review of research publicat
 ions in PubMed 2018 – 2023 in the field of heart failure that were present
 ed as developing clinical prediction models by their authors. The abstract
 ed data elements were based on those identified in PROBAST (Prediction mod
 el Risk of Bias ASsessment Tool) and TRIPOD (Transparent Reporting of a mu
 ltivariable prediction model for Individual Prognosis Or Diagnosis). We ev
 aluate the methodological conduct of the studies and present the sentiment
  analysis to estimate the prevalence of subjective or promotional language
  in the abstract corpus.Please join the event.About Larissa StanberryDr. S
 tanberry is an experienced statistician and a program director with profes
 sional focus on bridging the gap between biomedical research and clinical 
 practice. She completed her PhD in Statistics at the University of Washing
 ton in Seattle. Dr. Stanberry leads a cardiovascular research program at t
 he Minneapolis Heart Institute Foundation, a non-profit research institut
 e in Minneapolis, Minnesota. Her professional focus is on advancing clini
 cal research through rigorous statistical treatment of data. She has autho
 red and contributed to many scientific publications. Dr Stanberry also ser
 ves as a statistical editor of top tier research journals in cardiovascula
 r field (JACC Heart Failure and JACC Advances) and NASA Human Research Pro
 gram. \n\nContact Information: \n CANSSI \n115 Ottawa Road, Toronto, ON 
 \n\nCategories \n Data Science ARES \n\nAudiences \n FacultyGraduate Stude
 nts
DTSTART;TZID=America/New_York:20240429T153000
DTEND;TZID=America/New_York:20240429T163000
LAST-MODIFIED:20240410T132409Z
LOCATION:115 Ottawa Road, Toronto, ON
SUMMARY:Clinical Prediction Models – Signal or Noise? A Case of Heart Failu
 re
URL;TYPE=URI:https://www.statistics.utoronto.ca/events/clinical-prediction-
 models-%E2%80%93-signal-or-noise-case-heart-failure
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