The medical field is often on the forefront of new technology, with unexpected approaches to saving lives and fighting disease. Indeed, recent technologic advancements may be helping to solve long-standing issues in the healthcare community, like cancer care, data organization, and physician training.
With artificial intelligence (AI) allowing oncologists and radiologists to detect, diagnose, and tailor treatment plans for patients with cancer, the oncology field may be forever changed. Cloud-based systems take the capabilities of AI into the stratosphere, where smart systems are able to sort and store copious amounts of data to finally be organized in a more useful manner. Virtual reality is also allowing for extra surgical training, as well as piece of mind for patients prior to upcoming procedures.
The Newest Weapon in the War on Cancer
The idea of machines that can think for themselves has been around since the 1950s, and was articulated well in British computer scientist Alan Turing’s 1950 paper, Computing Machinery and Intelligence. Turing’s paper was not the first mention of AI but was a guiding light that contributed in part to the creation of a 1956 conference called the Dartmouth Summer Research Project on Artificial Intelligence.
Fast forward to the 21st century and AI is all around us, assisting in our daily lives in the form of Siri, Spotify recommendations, targeted advertisements, and more. The biggest breakthroughs in AI use may be in the medical field, where research teams worldwide are using these programs in a myriad of ways to assist cancer patients and doctors. For instance, an AI program developed at the University of Surrey in England predicts the severity of depression, anxiety, and sleep disturbance—all associated with decreased quality of life—in patients with cancer.
Google’s Lymph Node Assistant (LYNA) program is being used to help improve detection accuracy. LYNA is reported to have 99% accuracy, whereas human physicians are given to a much higher rate of mistakes. Systems like LYNA that reduce human error are especially promising, as time is invaluable in determining a cancer prognosis. For highly aggressive forms of cancer, this could be the difference between life and death. Rare cancers like mesothelioma are often misdiagnosed at first, leading to an average life expectancy of only 2 years after successful diagnosis. International teams have seen nearly 98% accuracy in using AI to diagnose malignant pleural mesothelioma, which can help improve a patient’s prognosis.
Cancer in the Sky With Data
Data shortage has never been the issue facing cancer researchers, as the disease has been devastating lives for nearly all of human history. The abundance of cancer-related is too vast for the human mind to reliably sort through and make use of, but machines are here to solve that problem. Memorial Sloan Kettering Cancer Center (MSK) shared its collection of 25 million tumor slides with Paige.AI, which uses the digitized data to train accurate programs. Real medical data is key to developing helpful AI machines, because fabricated data may lead to unintentional biases or failure.
The Cancer Genome Atlas (TCGA) represents an even larger dataset than MSK’s, with data on 33 tumor types, comprehensive information on thousands of patients, and more than 2.5 petabytes of information. The National Cancer Institute recognized the potential in this data as well as the need for a secure platform to access the information and created the Cancer Genome Cloud (CGC). The CGC allows researchers to collaborate on a cloud platform that’s fast and accessible. Other big names developing—or already deploying—cloud-based systems to collate cancer data include Intel, Google, and IBM.
Virtual Training, Real Expertise
Startup Surgical Theatre is helping to pioneer the practice of using virtual reality (VR) systems to train students, plan upcoming surgeries, explain procedures to patients, and guide surgeons during operations. The company was started with a simple and revolutionary idea: “What if surgeons could train like fighter pilots previewing their surgical procedure, much like a fighter pilot can pre-fly their mission?”
Top-notch academic hospitals like Stanford, Mount Sinai, and Mayo Clinic are currently using this technology. At Stanford, a VR system was used by Gary Steinberg, MD, PhD, to explain an impending aneurysm surgery to patient Sandi Rodoni. Rodoni reported feeling calmer after seeing her surgery plan via VR, knowing that her surgeon wouldn’t “run into any surprises.”
Training medical students and residents is another impactful capability of VR, which can be used for learning human anatomy, practicing surgeries, and administering exams. VR, and its sibling augmented reality, can be used to add to the experience without the risks of training on living patients.
Advancements in medical technology have the ability to save lives, reduce costs, and streamline the entire system. Keeping an eye on these developments is key to predicting how and where growth in this field will occur.