Good morning class. We've learned quite a bit about cancer and how it can develop in the body.
Today we are joined by a specialist in artificial intelligence who will be
speaking about how AI is being used to accelerate cancer research and therapy.
Hello everyone, I'm excited to be here. Before we begin, let's recap what cancer is. Are there
any student volunteers who would like to explain what you've learned so far?
Sure I'd like to! Cancer is a disease in which some of the body cells begin to grow
uncontrollably. Normally human cells grow and multiply through a process called cell division
when cells grow old or become damaged they die and new cells can take their place.
Sometimes this orderly process is disturbed and abnormal or damaged cells grow
and multiply when they shouldn't. These cells form what we call tumors or lumps of damaged tissues.
Yes, great explanation. So tumors can be of two types: malignant or benign. Malignant tumors
can spread across the body and form new tumors through a process called metastasis.
Benign tumors stay in one place and cannot invade nearby tissues. Benign tumors are generally larger
in size. But how do cells get damaged in the first place? Changes in the DNA called mutations can
result in damaged cells. This may be a result of errors during the DNA replication process of cell
division or it may be triggered by harmful substances such as the chemicals in tobacco,
or UV rays from the sun. Cancer treatment involves locating the tumor, determining
what type of cancer it is and then choosing a course of therapy to get rid of the tumor.
Now let's talk about artificial intelligence which is also known as AI.
AI systems are computer performance tasks that use algorithms to mimic a human's cognitive ability.
In order to develop these systems it requires a large amount of data sets which allows the
AI to find out the pattern within the data set, to identify the relationship between complex
features in the data.
Oh that's so cool, so how could AI be used in the context of cancer?
well you see AI could be applied to many areas of cancer research and therapy.
One important use is in cancer detection. When testing for cancer, imaging tests such as CT scans
MRIs or X-rays are taken to produce detailed images of the area where a tumor may have formed.
Traditionally, radiologists individually inspect each image to look for tumors. Now we can train
AI technology to analyze these images and detect cancer. Whoa that's really cool but why might we
use AI to detect cancer when we already have radiologists who are trained to interpret
medical images? Great question. So the goal of using AI to detect cancer is not about replacing
the jobs of radiologists but rather aiding them in establishing quicker and more accurate diagnoses,
because we know that when cancers are found early the prognosis is often much better for patients.
Even the most experienced clinicians make errors because the human eye is not perfect. AI has the
potential to be extremely accurate. For example, due to the power of deep learning a system was found
to be over 90 percent effective at detecting lung cancer spots. For comparison radiologists typically
average a 65 accuracy. That's amazing, are there any cases where a radiologist's expertise might
be more helpful though? Absolutely, since AI systems look for patterns based on the data sets that they
are trained against these systems are best at flagging the common or what we call textbook
cancer cases. One commentary highlights that human radiologists can more accurately diagnose the more
complex or unusual cancer cases. Now this is likely due to critical reasoning skills and
adaptability that can't quite be mimicked by AI just yet. Since thousands of cancer screening
tests are initiated each year it places a lot of burden on radiologists. AI could be used to flag
the common cases allowing radiologists more time and resources to focus on the more complex cases.
Interesting, can AI differentiate between different types of cancers? Yes it can actually.
So once the tumor has been located we can take a closer look at the micro environment and determine
what type of cancer it is. AI technology can make use of deep learning pattern recognition
to quickly scan through thousands of images and detect critical regions. These can help
it determine the exact type of cancer at a much faster rate than ever before. Wow that's impressive!
Can AI also figure out the exact mutation that occurred to cause cancer? Yes! So this is typically
done by genome sequencing which determines the exact sequence of DNA nucleotides in the genome.
AI can speed up this process by integrating this information with the processes in the cell to get
a holistic understanding of the mutated genes. For example, in one study, researchers trained
AI technology to classify lung cancer images as either having adenocarcinoma, squamous cell
carcinoma, or normal tissue. It was able to do this with a 97 percent accuracy. It was also able
to identify six of the most common genetic mutations, all within a 64 percent to 86 percent accuracy.
Wow that's very cool! I'm curious to know if AI can also pick up on other information from the images?
Good question. So AI can be used to characterize the tumor's microenvironment.
This is made up of the tumor cells, nearby cells, extracellular matrix and interstitial fluid. These
can all interact with the tumor cells, influence their phenotype as well as determine how the tumor
will evolve, move or respond to therapies. Using this information AI can help oncologists predict
outcomes for various types of cancer therapy and make informed decisions on next steps for therapy
and further analysis. This technology is evolving rapidly. Scientists are working on developing more
powerful multiplexed imaging platforms which are capable of detecting many aspects of the cell
micro environment at a much greater resolution which will allow researchers to study complex
cell to cell interactions in much more detail and at faster rates. Can you tell us more about some of
the ethical considerations we need to consider when implementing AI into healthcare settings?
There are absolutely ethical considerations to take into account. The first is confidentiality and
consent. Deep learning requires a large amount of confidential health data it is extremely difficult
to get every individual's consent to share their health records for the development of AI.
Another ethical consideration includes bias and transferability in AI.
As previously mentioned, AI is a learning system based on a massive data set to develop its ability.
However it is well recognized that many of our data sets do not adequately represent
diverse groups. Images taken from a very specific group in a very specific setting
may not necessarily be representative of all demographics. Interesting, these all sound like
very valid concerns that may be hard to find solutions for. Yes engineers and policy workers are
working to minimize the potential downsides of the technology before it's widely available for use.
All right class, that brings us to the end of this presentation
we've certainly learned quite a bit today and we're excited to see where artificial
intelligence will take us in the future. Thank you for sharing your knowledge and insight with us
It was my pleasure, now from one scientist to another, continue to stay curious and ask questions