A new artificial intelligence tool developed by the University of Toronto research team can significantly reduce the time required to develop a radiation plan for cancer patients.
Researchers use artificial intelligence to develop personalized cancer radiotherapy treatment plans for a total of 20 minutes
According to a paper published in the journal Medical Physics, the study used artificial intelligence to mine historical data on radiotherapy and design algorithms to develop recommended treatment strategies. To validate the relevant treatment plan generated by artificial intelligence, the researchers observed 217 patients with head/neck cancer who received a routine radiotherapy plan. It turns out that the plan proposed by artificial intelligence is basically the same as the regular plan.
Aaron Babier, a principal research member at the University of Toronto's engineering department, said, "There are many other artificial intelligence optimization engines out there, but we hope they will be closer to the specific requirements of existing clinical best practices."
For now, it can take several days to customize a radiotherapy plan for each patient. This is because cancer usually spreads and grows, so doctors need to invest a lot of time in designing these complex treatment strategies.
It is well known that cancer in the head/neck position has been a difficult point in the design of treatment plans because the tumor condition often varies greatly among different patients. Researchers hope that this tool will deliver good results in the tough and complex cancer category. Based on this, the tool is expected to play a better role in the case of tumor variability such as prostate cancer.
Combined with this problem, Babier stressed that AI should not become an alternative to healthcare professionals, but to help them save time by taking over all kinds of important basic work. Once the software creates a treatment plan, it still needs to be reviewed and further modified by radio physics experts, which can take at least several hours.
Artificial intelligence is widely regarded as an important future direction for cancer diagnosis, monitoring, and treatment, but some health care professionals raise ethical concerns about using machine learning tools to make clinical decisions. Earlier this year, Stanford University researchers and medical doctors raised the question in an article in the New England Journal of Medicine: "Doctors must fully understand how algorithms are created and evaluate them in a critical way. Create a data source of the predicted results, understand how the model works and prevent it from being overly dependent."
Nowadays, the development of new technologies in the medical world has become a universal trend – medical doctors need to combine these new diagnostic methods with their own expertise to fully understand the extent to which these new technologies determine the fate of patients. A similar debate is currently underway, including whether artificial intelligence should be used to biopsy cancer.
Despite these problems, the health care industry has begun to invest resources and energy in artificial intelligence. Major technology giants including Microsoft and IBM are also introducing artificial intelligence into various applications. Many companies seem to believe that artificial intelligence will be a viable solution that can effectively solve the long and costly problem of drug discovery. According to a survey conducted by BenchSci, a Toronto-based biotechnology company, 28 pharmaceutical companies and 97 startups are using artificial intelligence technology for drug discovery.
Babier explained that the goal of using artificial intelligence-assisted radiotherapy design is to further liberate the energy of medical personnel rather than bring about disruptive changes.
Babier pointed out that "this tool is essentially a very simple plug-in that helps provide assistance in a clinical setting, with the difference being that it has a higher level of intelligence."
The University of Toronto team is not the only research organization dedicated to using artificial intelligence to optimize radiotherapy programs. Other interested parties include Google's DeepMind Health, which is currently collaborating with the University Hospital in London.
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