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The given presentation showcases examples of how artificial intelligence technology can be used to improve the patient journey in the specific medical field of oncology.
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The practice of medicine involves diagnosis, treatment, and prevention of diseases. Recent technological breakthroughs have made little dent to the centuries-old system of practicing medicine: complex diagnostic decisions are still mostly dependent on “educated” work-ups of the doctors, and rely on somewhat outdated tools and incomplete data. All of this often leads to imperfect, biased, and, at times, incorrect diagnosis and treatment.
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Mental illness is common and disabling but the evidence is that fewer than half of people seek any treatment and few receive any help from specialized mental health professionals. In Canada, there are long waiting lists to see psychological therapists face to face despite the importance of non-drug therapies. One way to address this problem is to use computerized e-therapies which deliver structured mental health treatment via a computer. Dr. Simon Hatcher, Psychiatrist at The Royal's Community Mental Health Program and Vice Chair of Research for the Department of Psychiatry at the University of Ottawa, lead a discussion about the role of technology in mental health treatment. Highlights include: the effectiveness of online mental health treatments and opportunities for innovation and policy change in field of mental health.
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ML to Cure the World:
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Similar to Sentiment Analysis for Public Opinions in Healthcare_Redacted.pdf (20)
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Sentiment Analysis for Public Opinions in Healthcare_Redacted.pdf
1. Sentiment Analysis for Public
Opinions in Healthcare
Tassanee Lerksuthirat, PhD
(She/Her/Ning)
16-Aug-2023; 9.00-10.00
Research Center, Ramathibodi Hospital, Mahidol University
Using Python as a programming language to investigate!
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15. Take home messages
● Twitter – good sources to provide public opinions regarding healthcare
issues
○ Vaccinations
○ Cancers
○ Narcotic drugs
● Many Python based-libraries available to do data analysis
○ Scrape data
○ Cleaning data
○ Analysis
■ Gain insights of information
■ Create model for prediction
● Data-driven decision or better planning
○ Vaccine -- Increase rate of vaccinations
○ Cancers -- Improve patients’ perceptions
○ Narcotic drugs -- Raise awareness on the cannabis usage
16. Question to think about
● What are the limitations of these studies?
○ ……………….
○ ……………….
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