Artificial Intelligence in Cancer Treatment
The world has seen and heard enough about Artificial Intelligence and the wonders it has been helping us humans with and just when we thought AI could give us no more, there is news on how AI has been developed to tackle cancer therapy and treatment. Making the lives of cancer survivors better are AI technology, AI startups, and AI tech giants like Google Deepmind Health to name a few sources.
AI uses machine language, natural language processing, algorithms, computer vision, planning, artificial general intelligence to engage in learning complex patterns; find and understand differences; draw out pathways in creating easy, feasible and reliable solutions to the medical field. Robot-assisted surgeries that operate on AI are used by surgeons for delicate conditions with precision control. With the impactful entry of Artificial Intelligence, health care is getting better, faster diagnosis is a reality with hundreds of thousands of patient cases each year, personalized patient treatment and regimen are made available thanks to one powerful aspect of AI called machine learning (MI). Powerful and fool-proof algorithms will pinpoint illnesses and prescribe treatments while a machine is fed with a patient’s medical record and his/her family medical record to collect and use the massive collection of data. AI helps in planning the treatment and predicting tumor growth and evolution, drug resistance, side effects all from the data it already has access to or with the new data made available by researchers, online cancer care portals and health care personnel and medical professionals like doctors.
A new artificial intelligence (AI) tool developed by a team at the University of Toronto headed by Aaron Babies has developed software to significantly reduce the time needed to develop radiation therapy treatment plans for cancer patients. Historical radiation therapy is mined using the software and AI automates the process under twenty minutes. Data from clinical trials, drug research, drug discovery, image processing, image mapping, decoding raw data are all used in AI software.
Google’s Deepmind Health integrates the data and research collected from health centers from around the world and uses AI. Application of machine learning to screen mammograms is one of the few steps done by Deepmind Health since its entering The controversial scene of collecting patient data from the UK Imperial Centre. In the recent news, Deepmind has resorted to a bitcoin-style ledger-based system to record patient data and interaction automatically and is fully visible since it’s an online ledger.
MIT Media Lab has proposed a model that controls the treatment regimen it created by using “self-learning” machine learning that creates an optimal treatment plan, with the lowest possible potency and frequency of doses that reduce tumor sizes to a degree comparable to that of traditional regimens.
TriNet, a global health research network that optimizes clinical research and enables discoveries through the creation of real-world evidence, data, analytics, and a researcher community together. This company based in Cambridge, Massachusetts enables a global industry exchange and liberates data with the potential to rapidly provide answers to hard questions regarding clinical problems. It supports electronic medical records and genomics analysis on over 300 million patients from “hundreds” of health care institutions in 17 countries, including the U.S., U.K., Germany, Italy, Japan, Singapore, India, and Brazil. “ With TriNet, what previously took days or weeks to determine may often be done in minutes,” says Merck Global Health Innovation Fund vice president.
With around 1.6 million people diagnosed with cancer worldwide, AI acts as a revolutionary way to assist doctors, researchers, and surgeons to diagnose, layout treatment plans, review, and provide post-cancer care to patients. This does not mean AI is gaining more importance than the doctors and researchers but that robots and AI make life a little simpler and stress-free for both doctors and patients. The human connection will still be necessary for optimal patient care but the role of doctors in diagnostics may vary. It is an achievement that AI is what it is now from where we started it all from the “Turing test”. With deep learning, there is more scope in what AI could assist the cancer scene with and there is more hope in all the technological advancements that are yet to be seen.