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AI is helping doctors to manage vast volumes of data that are impossible to process by the human mind.
FREMONT, CA: Artificial Intelligence (AI) in healthcare is one of the emerging fields in today's world. AI has brought a paradigm shift to healthcare, driven by increased accessibility of information on and fast advancement in analytical methods. AI-enabled systems can help find connections that point to new ways of disease prevention, diagnosis, and treatment by streamlining the collection and analysis of vast amounts of data. Few concepts have caused as much enthusiasm or confusion in the last century as the advent of AI in oncology.
Today's journey to support and enhance the therapy of cancer through information, analytics, and AI, is still in the early phases. In reality, AI is not only used today to assist doctors in delivering cancer care, but it produces quantifiable outcomes while charting a course for the future.
AI helps doctors handle information that is too large for the human mind to process. The practical implementation of AI in radiology, pathology, and, dermatology, which involves image recognition, is well established. This technology can also help a doctor who may not remember the recent literature on a specific clinical situation by providing therapy alternatives for evaluation along with curated medical research.
AI can also be used to process the eligibility criteria of thousands of clinical trials and match patients to appropriate exams. The technology can also be used to quickly annotate the outcomes of tumor genome sequencing, identifying potentially personalized therapeutic alternatives for the patient.
This technology could be used to promote mutual decision-making between physician and patient, to enrich the debate of multidisciplinary tumor boards, medical education, and possibly distant consultation.
Based on outcomes from an ASCO research that analyzed 1,000 breast, lung, and colorectal cancer patients, it was discovered that when AI-driven treatment alternatives from Watson for Oncology were submitted to a multidisciplinary tumor board a group of doctors in various specialties who reviewed and discussed treatment alternatives for patients, they altered their treatment choices in 13.6 percent of instances based on the data supplied.
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In 55 percent of cases, AI provided recent evidence for new treatment options; in 30 percent of cases, the new options were more personalized, and in 15 percent of cases, new insights from phenotypic and genotypic data and evolving clinical experiences emerged from the technology.
This is such a significant collection of results as it demonstrates precisely where AI technology can add the most substantial value by complementing current medical procedures and bringing new data into the process of therapy choice that might not have been included otherwise.
Throughout these varied applications of AI to real-world cancer care around the world, the technology is gradually becoming described and understood but not as a replacement for doctors or a magic cure machine, but as a backstop to help caregivers and patients consider solutions to treatment and a tool for producing thoughts quickly.
The development of AI in the field of oncology is still early, and difficulties are yet to come. But based on the results of past years, there is convincing proof of the crucial role that this technology is already playing in improving how physicians choose to treat cancer worldwide.
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