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The healthcare industry has long been an early adopter of technological evolution and advancements. Off late, Machine Learning (ML, a subset of Artificial Intelligence [AI]) has started playing a key role in many healthcare related areas, including discovering links between genetic codes to improve patient outcomes, treatment of chronic diseases, healthcare specific power process automation or even for maximizing hospital operational efficiency. ML approach focuses on developing algorithms/ statistical models that can automatically estimate unseen patterns hidden in medical data.
Sebastian Thrum, a computer scientist and founder of Udacity once said “Just as machines made human muscles a thousand times stronger, ML (machine learning) will make the human brain a thousand times more powerful.”According to a latest survey, AI in healthcare market was valued at $4.8 billion in 2019 and is projected to reach $99.5 billion by 2027, registering a CAGR of 42.8% over the next seven years.
In one of my earlier blogs, I had mentioned that an appropriately designed and implemented AI/ ML solution could be a boon to healthcare organizations and had shared a few relevant use cases.
A team of data scientists & developers at Aress Software have built, tested and optimized predictive models that could assist healthcare providers with improved clinical decision-making:
Apart from these, Aress team has also been working on gnome clustering analysis, cardiovascular disease prediction, brain tumour analysis, diagnosis of liver disease & Alzheimer prediction models wherein apart from machine learning, deep learning techniques too are leveraged to improve prediction accuracy and outcomes.
The increasing intricacy and rise of available data in healthcare means that AI will increasingly be applied within the field. For more information about AI/ advanced analytics and benefits of implementing it for your organization, visit our website page for Artificial Intelligence and Advanced Analytics. And ask for free consultation by our AI/ advanced analytics experts or email us at AI@aress.com.
Category: Analytics, Artificial Intelligence, Big Data and BI