Five Ways Artificial Intelligence Benefits Cancer Treatment

Five Ways Artificial Intelligence Benefits Cancer Treatment

Artificial Intelligence (AI) can greatly benefit both cancer treatment providers and patients affected by the disease. This article will highlight five ways AI improves cancer treatment. We will start off by stating what AI IS NOT.

AI is not:

  • Robots doing your house work
  • Machines taking over the world and eliminating the human race
  • Devices making decisions for themselves, they follow processes defined by smart people.

“Right now, AI doesn’t have free will and certainly isn’t conscious — two assumptions people tend to make when faced with advanced or over-hyped technologies,” Mousavi said. “The most advanced AI systems out there are merely products that follow processes defined by smart people. They can’t make decisions on their own.”[i]

In machine learning (a subset of AI), which includes deep learning and neural networks, an algorithm is presented with boatloads of training data — examples of whatever it is that the algorithm is learning to do, labeled by people — until it can complete the task on its own. For facial recognition software, this means feeding thousands of photos or videos of faces into the system until it can reliably detect a face from an unlabeled sample. [ii]

So, what is AI? It is hard to define but commonly refers to a a group of iterative, “self-learning” techniques, which discover relationships within data that can evolve and often be performed faster over time. With Machine Learning (ML) being a subset of AI that refers to algorithms that are exposed to training data (massive amounts) and then are able to find hidden patterns and simplify or organize the data. Which is then used to perform a task, such as a diagnosis. Deep Learning (DL) algorithms can learn the optimal features that best fit unstructured data. AI powered by DL algorithms have made self-driving vehicles, mobile check deposit, UBER and other conveniences available to us.

Here are Five Ways AI can Benefit Cancer Treatment:

Cancer Imaging

Cancer Imaging is an area that the tools of AI have made a significant positive impact. Recently a study of an AI program analyzing 130,000 skin images was able to classify malignant lesions with higher sensitivity and specificity than a panel of 21 board-certified dermatologists…Researchers found that algorithms trained on colonoscopic images from 1290 patients, had a 94% rate in polyp detection[iii]

Guiding treatment choice

In today’s world, being able to effectively and accurately harness the power of data enables more efficient decision-making across most industries. Healthcare is no different. As healthcare providers begin to move towards a standardized format for recording patient outcomes, large sets of data will become available for analysis by AI-enabled systems which can track outcome patterns following treatment and identify optimal treatments based on patients’ profiles. In doing so, AI empowers clinical decision-making and ensures the right interventions and treatments are customized to each patient, creating a personalized approach to care. The immediate consequence of this will be a significant improvement in outcomes, which will eliminate costs associated with post-treatment complications – one of the key drivers of cost in most healthcare ecosystems across the world.

More efficient diagnosis

Repetitive, uncomplicated tasks such as the analysis of CT scans and certain tests can be performed more accurately by AI-enabled systems, reducing physician error and enabling early diagnosis and interventions before conditions become critical. As an example, an Israeli start-up has developed AI algorithms that are equally or more accurate than humans when it comes to the early detection of conditions such as, for example, coronary aneurysms, brain bleeds, malignant tissue in breast mammography and osteoporosis.

According to a recent article in Wired, AI has demonstrated 99% accuracy and is 30 times faster in reviewing and translating mammograms, enabling much earlier detection of breast cancer than humans are capable of. In cases such as osteoporosis, which costs the UK’s National Health Service approximately £1.5 billion annually (and that excludes the high costs of social care), the detection of vertebral fractures – an early indicator of impending osteoporosis which is commonly missed by human diagnosis – can substantially reduce the cost of this condition to health services.

In another case, Researchers analyzed existing data of the symptoms experienced by cancer patients during the course of computed tomography x-ray treatment. The team used different time periods during this data to test whether the machine learning algorithms are able to accurately predict when and if symptoms surfaced. The results found that the actual reported symptoms were very close to those predicted by the machine learning methods. This work has been a collaboration between the University of Surrey and the University of California in San Francisco (UCSF). The UCSF research in this joint collaboration is led by Professor Christine Miaskowski.[iv]

Payam Barnaghi, Professor of Machine Intelligence at the University of Surrey, said: “These exciting results show that there is an opportunity for machine learning techniques to make a real difference in the lives of people living with cancer. They can help clinicians identify high-risk patients, help and support their symptom experience and pre-emptively plan a way to manage those symptoms and improve quality of life.” [v]

Clinical trials optimization and drug development

AI has the potential to enable faster development of life-saving drugs, saving billions in costs that can be transferred to health ecosystems. Most recently, a start-up supported by the University of Toronto programmed a supercomputer with an algorithm that simulates and analyses millions of potential medicines to predict their effectiveness against Ebola, saving costly physical tests and – most importantly – lives, by repurposing existing drugs.[vi]

In clinical trials, AI can optimize drug development using biomarker monitoring platforms – biomarkers allow for gene-level identification of diseases – and millions of patient data points, which can be analyzed in seconds from a drop of blood using at-home devices. [vii]

Empowering the patient

AI has the potential to truly empower us as individuals to make better decisions regarding our health. Vast numbers of people across the world already use wearable technology to collect everyday information, from their sleep patterns to their heart rate. Applying machine learning to this data could inform people at risk of certain diseases long before that risk becomes critical. Mobile apps are already providing granular-level patient profile information that could help people living with specific chronic conditions to better manage their disease and live healthier lives. All of this can lead to healthier populations and a reduction of the overall cost burden. [viii]

These examples represent a small fraction of what is possible when the full potential of AI is leveraged in the delivery of healthcare. The possibilities can neither be underestimated nor overemphasized, and cooperation between public and private sector industry stakeholders is vital if this potential is to be realized. As global populations live longer and the prevalence of chronic disease increases, the rising cost of healthcare will continue to remain an important topic amongst healthcare stakeholders. [ix]

At Just4Cancer our broader mission includes providing you information on how cancer costs may be reduced. But in any case, people affected by cancer will need tools to educate themselves, communicate with each other and raise funds when needed. That is why we are here. We look forward to providing you the platform to accomplish these tasks.

[i] You Have No Idea What Artificial Intelligence Really Does
The world of AI is full of hype and deception.Futurism, 10/16/2018,

[ii]  You Have No Idea What Artificial Intelligence Really Does The world of AI is full of hype and deception.Futurism, 10/16/2018,

[iii] Artificial Intelligence in Oncology: Current Applications and Future Directions, ModernMedicine Network, 2/15/19

[iv] AI predicts cancer patients’ symptoms, ScienceDaily, 2/2/19,

[v] AI predicts cancer patients’ symptoms, ScienceDaily, 2/2/19,

[vi] Four ways AI can make healthcare more efficient and affordable, World Economic Forum, 5/2018,

[vii] Four ways AI can make healthcare more efficient and affordable, World Economic Forum, 5/2018,

[viii] Four ways AI can make healthcare more efficient and affordable, World Economic Forum, 5/2018,

[ix] Four ways AI can make healthcare more efficient and affordable, World Economic Forum, 5/2018,

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