Can Artificial Intelligence Help See Cancer in New Ways? (2022)

, by NCI Staff

Can Artificial Intelligence Help See Cancer in New Ways? (1)

Two identical black and white pictures of murky shapes sit side-by-side on a computer screen. On the left side, Ismail Baris Turkbey, M.D., a radiologist with 15 years of experience, has outlined an area where the fuzzy shapes represent what he believes is a creeping, growing prostate cancer. On the other side of the screen, an artificial intelligence(AI) computer program has done the same—and the results are nearly identical.

The black and white image is an MRI scan from someone with prostate cancer, and the AI program has analyzed thousands of them.

“The [AI] model finds the prostate and outlines cancer-suspicious areas without any human supervision,” Dr. Turkbey explains. His hope is that the AI will help less experienced radiologists find prostate cancer when it’s present and dismiss anything that may be mistaken for cancer.

This model is just the tip of the iceberg when it comes to the intersection of artificial intelligence and cancer research. While the potential applications seem endless, a lot of that progress has centered around tools for cancer imaging.

From x-rays of whole organs to microscope pictures of cancer cells, doctors use imaging tests in many ways: finding cancer at its earliest stages, determining the stage of a tumor, seeing if treatment is working, and monitoring whether cancer has returned after treatment.

Over the past several years, researchers have developed AI tools that have the potential to make cancer imaging faster, more accurate, and even more informative. And that’s generated a lot of excitement.

“There’s a lot of hype [around AI], but there’s a lot of research that’s going into it as well,” said Stephanie Harmon, Ph.D., a data scientist in NCI’s Molecular Imaging Branch.

That research, experts say, includes addressing questions about whether these tools are ready to leave research labs and enter doctors’ offices, whether they will actually help patients, and whether that benefit will reach all—or only some—patients.

What is artificial intelligence?

Artificial intelligence refers to computer programs, or algorithms, that use data to make decisions or predictions. To build an algorithm, scientists might create a set of rules, or instructions, for the computer to follow so it can analyze data and make a decision.

For example, Dr. Turkbey and his colleagues used existing rules about how prostate cancer appears on an MRI scan. They then trained their algorithm using thousands of MRI studies—some from people known to have prostate cancer, and some from people who did not.

(Video) Artificial Intelligence gives cancer research a boost.

With other artificial intelligence approaches, like machine learning, the algorithm teaches itself how to analyze and interpret data. As such, machine learning algorithms may pick up on patterns that are not readily discernable to the human eye or brain. And as these algorithms are exposed to more new data, their ability to learn and interpret the data improves.

Researchers have also used deep learning, a type of machine learning, in cancer imaging applications. Deep learning refers to algorithms that classify information in ways much like the human brain does. Deep learning tools use “artificial neural networks” that mimic how our brain cells take in, process, and react to signals from the rest of our body.

Research on AI for cancer imaging

Doctors use cancer imaging tests to answer a range of questions, like: Is it cancer or a harmless lump? If it is cancer, how fast is it growing? How far has it spread? Is it growing back after treatment? Studies suggest that AI has the potential to improve the speed, accuracy, and reliability with which doctors answer those questions.

Artificial Intelligence Aids Brain Tumor DiagnosisApproach diagnoses cancer in under 3 minutes during surgery.

“AI can automate assessments and tasks that humans currently can do but take a lot of time,” said Hugo Aerts, Ph.D., of Harvard Medical School. After the AI gives a result, “a radiologist simply needs to review what the AI has done—did it make the correct assessment?” Dr. Aerts continued. That automation is expected to save time and costs, but that still needs to be proven, he added.

In addition, AI could make image interpretation—a highly subjective task—more straightforward and reliable, Dr. Aerts noted.

Complex tasks that rely on “a human making an interpretation of an image—say, a radiologist, a dermatologist, a pathologist —that’s where we see enormous breakthroughs being made with deep learning,” he said.

But what scientists are most excited about is the potential for AI to go beyond what humans can currently do themselves. AI can “see” things that we humans can’t, and can find complex patterns and relationships between very different kinds of data.

“AI is great at doing this—at going beyond human performance for a lot of tasks,” Dr. Aerts said. But, in this case, it is often unclear how the AI reaches its conclusion, so it’s difficult for doctors and researchers to check if the tool is performing correctly.

Finding cancer early

Tests like mammogramsand Pap testsare used to regularly check people for signs of cancer or precancerouscells that can turn into cancer. The goal is to catch and treat cancer early, before it spreads or even before it forms at all.

Scientists have developed AI tools to aid screening tests for several kinds of cancer, including breast cancer. AI-based computer programs have been used to help doctors interpret mammograms for more than 20 years, but research in this area is quickly evolving.

One group created an AI algorithm that can help determine how often someone should get screened for breast cancer. The model uses a person’s mammogram images to predict their risk of developing breast cancer in the next 5 years. In various tests, the model was more accurate than the current tools used to predict breast cancer risk.

(Video) Artificial Intelligence: A Revolution for Cancer Screening & Detection

NCI researchers have built and tested a deep learning algorithm that can identify cervical precancers that should be removed or treated. In some low-resource settings, health workers screen for cervical precancer by inspecting the cervix with a small camera. Although this method is simple and sustainable, it is not very reliable or accurate.

Mark Schiffman, M.D., M.P.H., of NCI’s Division of Cancer Epidemiology and Genetics, and his colleagues designed an algorithm to improve the ability to find cervical precancers with the visual inspection method. In a 2019 study, the algorithm performed better than trained experts.

For colon cancer, several AI tools have been shown in clinical trials to improve the detection of precancerous growths called adenomas. However, because only a small percentage of adenomas turn into cancer, some experts are concerned that such AI tools could lead to unnecessary treatments and extra tests for many patients.

Detecting cancer

AI has also shown the potential to improve cancer detection in people who have symptoms. The AI model developed by Dr. Turkbey and his colleagues in NCI’s Center for Cancer Research, for instance, could make it easier for radiologists to pick out potentially aggressive prostate cancer on a relatively new kind of prostate MRI scan, called multiparametric MRI.

Can Artificial Intelligence Help See Cancer in New Ways? (3)

Although multiparametric MRI generates a more detailed picture of the prostate than a regular MRI, radiologists typically need years of practice to read these scans accurately, leading to disagreements between radiologists looking at the same scan.

The NCI team’s AI model “can make [the learning] curve easier for practicing radiologists and can minimize the error rate,” Dr. Turkbey said. The AI model could serve as “a virtual expert” to guide less-experienced radiologists learning to use multiparametric MRI, he added.

For lung cancer, several deep learning AI models have been developed to help doctors find lung cancer on CT scans. Some noncancerous changes in the lungs look a lot like cancer on CT scans, leading to a high rate of false-positive test results that indicate a person has lung cancer when they really don’t.

Experts think that AI may better distinguish lung cancer from noncancerous changes on CT scans, potentially cutting the number of false positives and sparing some people from unneeded stress, follow-up tests, and procedures.

For example, a team of researchers trained a deep learning algorithm to find lung cancer and to specifically avoid other changes that look like cancer. In lab tests, the algorithm was very good at ignoring noncancerous changes that look like cancerand good at finding cancer.

Choosing cancer treatment

Doctors also use imaging tests to get important information about cancer, such as how fast it is growing, whether it has spread, and whether it is likely to come back after treatment. This information can help doctors choose the most appropriate treatment for their patients.

A number of studies suggest that AI has the potential to gather such prognostic information—and maybe even more—from imaging scans, and with greater precision than humans currently can. For example, Dr. Harmon and her colleagues created a deep learning model that can determine the likelihood that a patient with bladder cancer might need other treatments in addition to surgery.

(Video) Using artificial intelligence to improve cancer care

Doctors estimate that around 50% of people with tumors in the bladder muscle (muscle-invasive bladder cancer) have clusters of cancer cells that have spread beyond the bladder but are too small to detect with traditional tools. If these hidden cells aren’t removed, they can continue growing after surgery, causing a relapse.

Chemotherapy can kill these microscopic clusters and prevent the cancer from coming back after surgery. But clinical trials have shown that it’s hard to determine which patients need chemotherapy in addition to surgery, Dr. Harmon said.

“What we would like to do is use this model before patients undergo any sort of treatment, to tell which patients have cancer with a high likelihood of spreading, so doctors can make informed decisions,” she explained.

Can Artificial Intelligence Help See Cancer in New Ways? (4)

The model looks at digital images of primary tumortissue to predict whether there are microscopic clusters of cancer in nearby lymph nodes. In a 2020 study, the deep learning model proved to be more accurate than the standard way of predicting whether bladder cancer has spread, which is based on a combination of factors including the patient’s age and certain characteristics of the tumor.

More and more, genetic information about the patients’ cancer is being used to help select the most appropriate treatment. Scientists in China created a deep learning tool to predict the presence of key gene mutations from images of liver cancer tissue—something pathologists can’t do by just looking at the images.

Their tool is an example of AI that works in mysterious ways: The scientists who built the algorithm don’t know how it senses which gene mutations are present in the tumor.

Are AI tools for cancer imaging ready for the real world?

Although scientists are churning out AI tools for cancer imaging, the field is still nascent and many questions about the practical applications of these tools remain unanswered.

Using AI to Classify Lung Cancer TypesThe computer program can differentiate the two most common forms of lung cancer.

While hundreds of algorithms have been proven accurate in early tests, most haven’t reached the next phase of testing that ensures they are ready for the real world, Dr. Harmon said.

That testing, known as external or independent validation, “tells us how generalizable our algorithm is. Meaning, how useful is it on a totally new patient? How does it perform on patients from different [medical] centers or different scanners?” Dr. Harmon explained. In other words, does the AI tool work accurately beyond the data it was trained on?

(Video) Can Artificial Intelligence Help Doctors Make Better Decisions?

AI algorithms that pass rigorous validation testing in diverse groups of people from various areas of the world could be used more widely, and therefore help more people, she added.

In addition to validation, Dr. Turkbey noted, clinical studies also need to show that AI tools actually help patients, either by preventing people from getting cancer, helping them live longer or have a better quality of life, or saving them time or money.

But even after that, Dr. Aerts said, a major question about AI is: “How do we make sure that these algorithms keep on working and performing well for years and years?” For example, he said, new scanners could change features of the image that an AI tool relies on to make predictions or interpretations, he explained. And that could change their performance.

There are also questions about how AI tools will be regulated. Upwards of 60 AI-based medical devices or algorithms have earned FDA approval as of 2020. But even after they are approved, some machine learning algorithms shift as they are exposed to new data. In 2021, FDA issued a framework for monitoring AI technologies that have the ability to adapt.

There are also concerns about the transparency of some AI tools. With some algorithms, like the one that can predict gene mutations in liver tumors, scientists don’t know how it reaches its conclusion—a conundrum known as the “black box problem.” Experts say this lack of transparency prohibits critical checks for biases and inaccuracies.

A recent study, for example, showed that a machine learning algorithm trained to predict cancer outcomes zeroed in on the hospital where the tumor image was taken, rather than the patient’s tumor biology. Although that algorithm isn’t used in any medical settings, other tools trained in the same way could have the same inaccuracy, the researchers warned.

There are also worries that AI could worsen gaps in health outcomes between privileged and disadvantaged groups by exacerbating biases that are already baked into our medical system and research processes, said Irene Dankwa-Mullan, M.D., M.P.H., deputy chief health equity officer of IBM Watson Health.

These biases are deeply embedded in the data used to create AI models, she explained at the 2021 American Association for Cancer Research Science of Cancer Health Disparities conference.

For instance, a handful of medical algorithms have recently been shown to be less accurate for Black people than for White people. These potentially dangerous shortcomings stem from the fact that the algorithms were mainly trained and validated on data from White patients, experts have noted.

On the other hand, some experts think AI could improve access to cancer care by bringing expert-level care to hospitals that lack specialists.

“What [AI] can do is, in a setting where there are physicians who maybe don’t have as much expertise, potentially it can bring their performance up to an expert level,” explained Dr. Harmon.

Some AI tools could even bypass the need for sophisticated equipment. The deep learning algorithm for cervical cancer screening developed by Dr. Schiffman, for example, relies on cell phones or digital cameras and low-cost materials.

Despite these concerns, most researchers are optimistic for the future of AI in cancer care. Dr. Aerts, for example, believes these hurdles are surmountable with more work and collaboration between experts in science, medicine, government, and community implementation.

(Video) How AI is making it easier to diagnose disease | Pratik Shah

“I think [AI technologies] will eventually be introduced into the clinic because the performance is just too good and it’s a waste if we don’t,” he said.

FAQs

How accurate is AI detecting cancer? ›

When tested on 44,755 completed ultrasound exams, the AI tool increased radiologists' ability to accurately identify breast cancer by 37 percent. Additionally, the tool helped to reduce the number of tissue samples and biopsies necessary to confirm tumors by 27 percent.

What technology can help detect cancer early? ›

Gamma Medica Inc.'s LumaGEM® digital molecular breast imaging system enables radiologists to detect early-stage cancers that can be missed in women with mammographic dense breast tissue. Dune Medical Devices' MarginProbe® System delivers real-time assessment of excised tissue in breast cancer surgery.

Are artificial intelligence systems useful in breast cancer screening programs? ›

AI could also reduce the workload of breast screening by reducing the effort needed to read thousands of mammograms for instance by replacing one of the mammogram readers. But there is also concern that AI may detect changes which would never cause the woman any harm.

How does AI detect breast cancer? ›

A major new study in Radiology shows that artificial intelligence (AI) is a promising tool for breast cancer detection in screening mammography programs. Mammograms acquired through population-based breast cancer screening programs produce a significant workload for radiologists.

Is AI used to detect cancer? ›

Scientists have developed AI tools to aid screening tests for several kinds of cancer, including breast cancer. AI-based computer programs have been used to help doctors interpret mammograms for more than 20 years, but research in this area is quickly evolving.

How can AI cure cancer? ›

AI can manage the use of chemotherapy drugs and predict the tolerance of chemotherapy drugs, so as to optimize the chemotherapy regimen. AI can help doctors make correct treatment decisions, reduce unnecessary surgeries, and help oncologists improve patients' cancer treatment plans.

What is the latest technology for cancer? ›

As a possible new technology for cancer treatment, gene editing with CRISPR takes months, not a year or two, to genetically modify T cells. That may mean much faster treatment for patients. The potential for genetic medicine is groundbreaking. Altering parts of DNA can redefine how your body fights off cancer.

What is the best scan to detect cancer? ›

A CT scan (also known as a computed tomography scan, CAT scan, and spiral or helical CT) can help doctors find cancer and show things like a tumor's shape and size. CT scans are most often an outpatient procedure. The scan is painless and takes about 10 to 30 minutes.

Which technology is used to early diagnosis of disease? ›

Techniques such as recombinant DNA technology, PCR and ELIZA help in early diagnoses of diseases.

What is Artificial Intelligence in mammography? ›

AI increases productivity

By detecting and characterizing abnormalities on mammograms, or indicating their absence, AI-based algorithms allow breast imagers to move faster through cancer-free cases and give more attention to the images with suspicious findings.

What do aromatase inhibitors do? ›

Aromatase inhibitors (AIs) lower estrogen levels by stopping an enzyme in fat tissue (called aromatase) from changing other hormones into estrogen. (Estrogen can fuel the growth of breast cancer cells.) These drugs don't stop the ovaries from making estrogen.

What exactly AI means? ›

artificial intelligence (AI), the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.

What is female breast? ›

(brest) Glandular organ located on the chest. The breast is made up of connective tissue, fat, and breast tissue that contains the glands that can make milk. Also called mammary gland.

How does hormone therapy for breast cancer work? ›

Hormone therapy (also called hormonal therapy, hormone treatment, or endocrine therapy) slows or stops the growth of hormone-sensitive tumors by blocking the body's ability to produce hormones or by interfering with effects of hormones on breast cancer cells.

How does AI detect skin cancer? ›

Hence, to aid in diagnosing skin cancer, artificial intelligence (AI) tools are being used, including shallow and deep machine learning–based methodologies that are trained to detect and classify skin cancer using computer algorithms and deep neural networks.

Which medical company uses AI in cancer detection? ›

Imagene AI is one of the notable companies in the field of AI-based precision medicine for cancer. The precision oncology diagnosis company from Tel Aviv uses proprietary deep learning algorithms to reduce the time required for biomarkers detection from several weeks to two minutes.

How is artificial intelligence used in medicine? ›

Artificially intelligent computer systems are used extensively in medical sciences. Common applications include diagnosing patients, end-to-end drug discovery and development, improving communication between physician and patient, transcribing medical documents, such as prescriptions, and remotely treating patients.

What is artificial intelligence in oncology? ›

AI identifies potential new drugs within a short time period at an affordable cost [69]. Drug testing can simulate and predict the effectiveness of cancer therapies leading to better results in in vivo experiments [70], which in turn would accelerate clinical research.

What are applications of artificial intelligence? ›

Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
...
What are examples of AI technology and how is it used today?
  • Automation. ...
  • Machine learning. ...
  • Machine vision. ...
  • Natural language processing (NLP). ...
  • Robotics. ...
  • Self-driving cars.

What is cancer biology? ›

(KAN-ser) A term for diseases in which abnormal cells divide without control and can invade nearby tissues. Cancer cells can also spread to other parts of the body through the blood and lymph systems.

What is the future of cancer research? ›

New insights into tumor immunology and biology, combined with advances in artificial intelligence, nano tools, genetic engineering and sequencing — to name but a few — promise ever-more-powerful capabilities in the prevention, diagnosis and personalized treatment of cancer.

How are most cancers discovered? ›

Biopsy. In most cases, doctors need to do a biopsy to diagnose cancer. A biopsy is a procedure in which the doctor removes a sample of tissue. A pathologist looks at the tissue under a microscope and runs other tests to see if the tissue is cancer.

What cancer is closest to finding a cure? ›

5 Curable Cancers
  • Prostate Cancer.
  • Thyroid Cancer.
  • Testicular Cancer.
  • Melanoma.
  • Breast Cancer -- Early Stage.
7 Dec 2021

What machines are used to detect cancer? ›

Imaging tests used in diagnosing cancer may include a computerized tomography (CT) scan, bone scan, magnetic resonance imaging (MRI), positron emission tomography (PET) scan, ultrasound and X-ray, among others.

Can blood tests detect cancer? ›

Most blood tests aren't used on their own to diagnose cancer. But they can provide clues that may lead your health care team to make the diagnosis. For most types of cancer, a procedure to remove a sample of cells for testing is often needed to be sure.

Can you wear a bra during an MRI? ›

Depending on which part of your body is being scanned, you may need to wear a hospital gown during the procedure. If you don't need to wear a gown, you should wear clothes without metal zips, fasteners, buttons, underwire (bras), belts or buckles.

Which technique is used for early detection? ›

So, the correct answer is 'R-DNA technology'.

Which of the following techniques early detection is not possible? ›

<br> Using conventional methods of diagnosis (serum and urine analysis, etc.) carly detection is not possible. <br> Recombinant DNA technology, Polymerase Chain Reaction (PCR) and Enzyme Linked ImmunoSorbent Assay (ELISA) are some of the techniques that serve the purpose of early diagnosis.

How recombinant DNA technology is helpful in diagnosis of disease? ›

Recombinant DNA procedures have now been applied to the problem of the identification of molecular defects in man that account for heritable diseases, somatic mutations associated with neoplasia, and acquired infectious disease. Thus recombinant DNA technology has rapidly expanded our ability to diagnose disease.

Is a mammogram accurate? ›

A mammogram is an excellent tool for finding breast cancer, particularly in women age 50 and over. Breast cancer is accurately diagnosed through mammography in about 78% of all women tested, while diagnostic accuracy rises to about 83% for women over 50.

What foods are estrogen blockers? ›

Cruciferous Vegetables

Packed within cruciferous veggies are phytochemicals that block the production of estrogen, allowing them to be an effective addition to an anti-estrogen diet. This group of vegetables includes kale, broccoli, cauliflower, Brussels sprouts, and arugula.

What foods are aromatase inhibitors? ›

Below, we share some foods that have been shown to inhibit aromatase activity.
  • Oats.
  • Artichokes.
  • Radishes.
  • Parsley.
  • Hot peppers.
  • Tangerines and oranges.
  • Pomegranates and pomegranate juice.
6 Feb 2022

How can I increase my aromatase naturally? ›

Foods Rich in Vitamin D and Calcium

Vitamin D plays a significant role in regulating calcium levels, and it's this role that may boost aromatase activity, say scientists. Researchers conducted an experiment on animals that lacked vitamin D receptors and in turn had low ovarian estrogen production.

How accurate is CT scan for cancer? ›

A Research-Based Answer. No single imaging test is 100% accurate in detecting abnormalities. There may be a misdiagnosis due to the quality of the scan or due to the expert reading the scan.

How accurate is CT scan for lung cancer? ›

The study was presented at the annual meeting of the American Society of Clinical Oncology. The second CT scan produced false-positive results for cancer in 33% of patients. That's more than twice the 15% false-alarm rate associated with X-rays, Croswell says.

Which medical company uses AI in cancer detection? ›

Imagene AI is one of the notable companies in the field of AI-based precision medicine for cancer. The precision oncology diagnosis company from Tel Aviv uses proprietary deep learning algorithms to reduce the time required for biomarkers detection from several weeks to two minutes.

What machine can detect cancer? ›

Imaging tests used in diagnosing cancer may include a computerized tomography (CT) scan, bone scan, magnetic resonance imaging (MRI), positron emission tomography (PET) scan, ultrasound and X-ray, among others. Biopsy. During a biopsy, your doctor collects a sample of cells for testing in the laboratory.

What is the best scan to detect cancer? ›

A CT scan (also known as a computed tomography scan, CAT scan, and spiral or helical CT) can help doctors find cancer and show things like a tumor's shape and size. CT scans are most often an outpatient procedure. The scan is painless and takes about 10 to 30 minutes.

Can too many CT scans cause cancer? ›

The typical CT radiation dose is 10 to 20 millisieverts (mSv), which is associated with a lifetime risk of fatal cancer of approximately one per 2,000 CT scans.

What cancers do not show up on CT scan? ›

Some cancers, such as prostate cancer, uterine cancer, and certain liver cancers, are pretty much invisible or very hard to detect on a CT scan. Metastases to the bone and brain also show up better on an MRI.

Why do non smokers get lung cancer? ›

Lung cancer can be caused by many risk factors other than smoking cigarettes, pipes, or cigars. These risk factors include exposure to other people's smoke (called secondhand smoke), radon, air pollution, a family history of lung cancer, and asbestos.

Why do some smokers not get lung cancer? ›

May 12, 2022 – Some smokers might not get lung cancer because of their DNA, researchers report in a new study. These people have genes that help limit mutations, or changes, to DNA that would turn cells malignant and make them grow into tumors, the researchers say.

Is lung cancer curable if caught early? ›

As with many other cancers, a key to surviving lung cancer is catching it in its earliest stages, when it is most treatable. For patients who have small, early-stage lung cancer, the cure rate can be as high as 80% to 90%.

What are the types of artificial intelligence? ›

These three types are: Artificial Narrow Intelligence. Artificial General Intelligence. Artificial Super Intelligence.

How does AI work in healthcare? ›

A common use of artificial intelligence in healthcare involves NLP applications that can understand and classify clinical documentation. NLP systems can analyze unstructured clinical notes on patients, giving incredible insight into understanding quality, improving methods, and better results for patients.

Who is leading AI in healthcare? ›

1) Google Health/DeepMind.

How is cancer detected? ›

Cancer is nearly always diagnosed by an expert who has looked at cell or tissue samples under a microscope. In some cases, tests done on the cells' proteins, DNA, and RNA can help tell doctors if there's cancer. These test results are very important when choosing the best treatment options.

How can you detect cancer at home? ›

6 At-Home Cancer Screening Tests
  1. Guaiac Fecal Occult Blood Test (gFOBT) for Colon Cancer. ...
  2. Fecal Immunohistochemical Test (FIT) for Colon Cancer. ...
  3. Stool DNA Test for Colon Cancer. ...
  4. Home Screening Test for Breast and Ovarian Cancer. ...
  5. Low-tech Test: Breast Self-Exam (BSE) ...
  6. Low-tech Test: Skin Cancer Self-Check.

When was cancer first diagnosed? ›

Our oldest description of cancer (although the word cancer was not used) was discovered in Egypt and dates back to about 3000 BC. It's called the Edwin Smith Papyrus and is a copy of part of an ancient Egyptian textbook on trauma surgery.

Videos

1. Can Artificial Intelligence Aid in Seeing Cancer in New Ways? | PIVOT AI Tool
(Family Care Hospitals)
2. Detecting cancer in real-time with machine learning
(Google)
3. How BioNTech is using Artificial Intelligence to find a Cancer Cure
(AI News)
4. How machine learning changes cancer research
(KochInstituteMIT)
5. What is artificial intelligence and what does it mean for cancer research? With Professor Chris Yau
(Ovarian Cancer Action UK)
6. #BenchToBedside: Diagnosing Cancer with Artificial Intelligence
(The University of Kansas Cancer Center)

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