One of the latest AIMed Breakfast Briefings: Effectively analy
Layers of information for a change
Of which, Dr. Chang highlighted the lack of progress in the area over the past decades as most sub-specialty meetings he attended over the years, focused more or less on the same debates or controversies. The need to come up with answers to these questions means there is a need to do something different. Although the industry is gradually evolving from evidence-based medicine to precision medicine and population health, there remains a huge knowledge gap.
Dr. Chang suggested to stack layers of
Pulling resources together for progress
Emily Paul, Head of Subject Matter Experts, SOPHiA GENETICS, agreed. She said this is what her company is trying to achieve at the moment: to integrate medical systems and decentralize information at a national level. It is crucial to pull in all the genomics information and human experiences in explaining what technology can actually do and minimize errors.
Likewise, Mayur Saxena, machine learning (ML) engineer and Chief Executive Officer of Droice Labs recalled his story as a Ph.D. student a few years ago working with clinicians to use ML on rare disease. Although the project demonstrated some preliminary results, there was no way they could recruit sufficient patients to test the solution. That was when he realized the importance to use existing data, to cohort individuals with ML and find out their chances of suffering from a rare medical condition and reduce the time for diagnosis.
In spite of knowing the need, speakers believe the present infrastructure and policy are not adequately supporting us to obtain more data. The focus on the hype of AI, rather than the long-term development, only aggravate the challenge.
More education is required for a cultural shift
Speakers urged for medical education reform. Better still, as suggested by Adam Kalawi, second-year Children Neurology Resident Physician at the University of California, San Diego Rady Children’s Hospital, to gather groups of multi-disciplinary individuals with very specific knowledge, to meet in the same room and discuss a particular topic. So, different professionals understand one another’s difficulties and offer solutions.
At the same time, Dr. Chang said people ought to reflect whether new technologies are truly taking a toll on the medical system. As a practitioner, Dr. Chang thought many tests and medical procedures often go into waste and patients and their families may not fully understand what these tests or medical procedures mean to them. As such, teaching patients and their families how AI and new technologies could possibly overcome such inefficiency is just as important as introducing a medical education transform.
At the end of the day, the roles of medical professionals are likely to be configured to a higher level. If we continue to think that AI or new technologies won’t work, it will just turn into a self-fulfilling prophecy. As such, the cultural shift within the medical and healthcare community should begin by looking at what others had done with AI and how they can be adopted into the setting.
A science writer with data background and an interest in the current affair, culture,