While words such as cancer and tumour trigger unpleasant feelings and concerns, it is vital to raise awareness on the rising incidence of cancer, preventive measures to tackle the disease, key symptoms to look out for and various treatments available.
Where do we stand
• India has around 2.25 million cases
• Over one lakh new cases are registered every year
• The Indian Council of Medical Research estimates that India is likely to register over 17 lakh new cases and over eight lakh deaths by end of 2020
Early detection is key
• More than 80 percent of ovarian, lung, prostate and breast cancer-related mortalities are completely avoidable if detected early
How AI is driving diagnosis
• It ensures quick turnaround time, greater accuracy and error-free results
• Machine Learning and Artificial Intelligence (AI) technologies automate the existing diagnostic procedures, aid doctors in report interpretation, and greatly reduce errors in communication
The term artificial intelligence came about in 1956, and since then, it has evolved immensely. AI is amplifying care for patients with chronic diseases by transforming the way they are diagnosed as well as treated.
The three forms of AI which play a major role in transforming cancer care are: Machine Learning, Deep Learning and Big Data. It is pretty evident that AI smartens up cancer care by interpreting data for a better understanding of cancer mechanisms (from common to rare cancers), offering plausible evidence base through Big Data sets and enhancing cancer treatments through analysis of best practices and trend.
It refers to a machine’s potential to swiftly evaluate data and discover patterns, thus extracting information from the data in order to further make informed decisions
A more refined version, it does not require any human intervention for the machine to function seamlessly. It plays a vital role in early detection of cancer.
This technology helps go into micro-details of a specific cancer. Hence, patients won’t be given unnecessary drugs thereby avoiding any adverse secondary effects. Despite advances in AI, there will always be some differences between human and technological execution. Healthcare providers need to adapt to AI. The technology can complement them in making more accurate clinical decisions or even replace human judgement in some functional areas. But a technology-driven bot or machine cannot be receptive to emotional quotients. At present, AI is majorly receptive to structured data in specific formats.
Currently, many AI applications analyse data generated from diagnostic procedures such as imaging, genetic testing and electro-diagnosis and can also provide suggestive actions in a predictive manner with greater granularity. It is an exciting phase of technological transformation as we’ll see AI exhibiting intelligent behaviours to understand human characteristics. The author is Founder and CEO, CORE Diagnostics
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