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FEATURE:

AC Observations
05/02/2023


MAJOR TAKEAWAYS FOR THE CLINICAL AND SCIENCE RESEARCHER (PART II)

Author: Anthony Chang, MD, MBA, MPH, MS

I am a pediatric cardiologist and have cared for children with heart disease for
the past three decades. In addition, I have an educational background in
business and finance as well as healthcare administration and global health – I
gained a Masters Degree in Public Health from UCLA and taught Global Health
there after I completed the program.



“There will be abuses of power that involve AI, just as there will be advances
in science and humanitarian efforts that also involve AI. Unfortunately, there
are certain trend lines that are likely to create massive instability.” 

Danah Boyd, Principal researcher for Microsoft

Wisdom involves applying knowledge and using judgment and insight for relatively
nuanced and complex situations. This highest level of the data-to-wisdom
hierarchy is still a human endeavor. Perhaps with “super” information resources
like the large language models that have recently arrived, knowledge and
intelligence as well as wisdom can be expedited in healthcare to improve the
Quintuple Aim.

AI in biomedicine failed in earlier eras, mainly due to a lack of computational
speed and big data. The result was an undesired disruption to clinicians’
workflow. This disadvantage of slowing down the work process coupled with a lack
of large volumes of data created unfavorable deployment. The clinicians back
then preferred not to use these AI tools even though the performance of was good
and even superior to groups of consultants.

The recent re-emergence of artificial intelligence this past decade after two
previous “winters” resulted from a convergence of advanced algorithms, cloud
computing, and computational power as well as big data. These elements all
improved dramatically in the past decade, and this convergence has accelerated
the progress of AI as well as raised the expectations of AI in healthcare for
the future.

Most healthcare data is unstructured (without tables with rows and columns) and
has been synthesized only in the last 5-10 years. Data is the foundational layer
of the data-information-knowledge-intelligence-wisdom pyramid. Good data science
and artificial intelligence projects will need good quality data that is
relatively complete and accurate. Big data (volume, velocity, variety, and
veracity) is exponentially increasing especially with genomic data and
real-world data.  

Real-world data (RWD) and real-world experience (RWE) are becoming more relevant
in clinical research. They can be very complementary to traditional data
collected in randomized controlled trials (RCT) and clinical research
registries. While RCTs focus on efficacy and safety with an experimental type of
study with intensive monitoring and follow-up, RWD and RWE focus on
effectiveness and value with an observational study with variable amounts of
monitoring and duration of follow-up.

Most time on a healthcare ML/AI project is spent on data access, collection, and
processing. While the algorithm design and model deployment can also be
time-consuming, this later step is less cumbersome than the initial phase of
curating the healthcare data. The very first step of the ML workflow, however,
should always be the formulation of a clinically relevant question with
potential impact (avoiding type III error- testing the wrong or irrelevant
hypothesis). 

The importance of these observations of artificial intelligence in healthcare
will be part of the topics of discussion at the in-person AIMed Global Summit
2023 scheduled for June 4-7th of 2023 in San Diego. The remainder of the week
will be other exciting AI in medicine events like the Stanford AIMI Symposium on
June 8th. Book your place now!

We at AIMed believe in changing healthcare one connection at a time. If you are
interested in discussing the contents of this article or connecting, please drop
me a line – anthony@ai-med.io 


LATEST POSTS

AC Observations

ARTIFICIAL INTELLIGENCE IN BIOMEDICAL RESEARCH: MAJOR TAKEAWAYS FOR THE CLINICAL
AND BASIC SCIENCE RESEARCHER (PART IV)

05/23/2023
Find out more
AC Observations

MAJOR TAKEAWAYS FOR THE CLINICAL AND SCIENCE RESEARCHER (PART I)

04/25/2023
Find out more

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