As a hot technology, AI is seen and developed by major industries, and the medical industry is no exception. The world's largest management consulting firm said that AI is expected to create huge savings for the United States by 2026.
Often, it is mentioned that arTIficial intelligence (AI) will discuss how it will make our technology equipment better, how to lead a driverless car, and even a world war. But in the medical industry, AI can greatly improve medical efficiency and quality. Algorithms, image recognition technology, natural language processing, and other AI technologies can ultimately make medical costs cheaper, reduce the time it takes to develop new drugs, and even help doctors diagnose diseases.
Faster drug development
It usually takes an average of 10 to 15 years for a pharmaceutical company to develop a new drug. Some companies, including IBM, point out that AI can reduce the time it takes to find new drugs by screening for genetic and clinical big data.
IBM said that Watson for Drug Discovery uses natural language processing to enable the platform to read millions of pages of unstructured data, understand nouns, related entities, interrelated verbs and prepositions to understand contextual meaning.
For example, the Barrow Institute of Neurology used Watson for Drug Discovery to identify unidentified genes and proteins that may be involved in amyotrophic lateral sclerosis (ALS). A few months later, Watson discovered five RNA-binding proteins (RBPs) that were never thought to be associated with ALS. In a recent paper published in the journal Acta Neuropathologica, Barrow researchers pointed out: "Overall, we have successfully used IBM Watson to help identify other RBPs associated with ALS, showing that AI can accelerate ALS and other complex nerves. Scientific research and development of systemic diseases."
Some drug makers have placed their bets on such AIs. In 2017, the famous pharmaceutical company GlaxoSmithKline said that this method of researching a disease target and then finding a molecularly targeted drug can reduce the drug development time from five and a half years to one year. AI can not only reduce the time required to develop drugs, but also reduce costs.
Assist in diagnosis
Harvard University pathologists have recently created an AI system that will help them diagnose breast cancer more accurately. AI technology helps doctors increase accuracy from 96% to 99.5%. This slight increase is significant because it means that between 68,000 and 130,000 women will get a more accurate diagnosis each year.
Similarly, oncologists at the University of North Carolina's Lineberger Comprehensive Cancer Center tested IBM Watson's genomics. Watson studied 1018 cases, and the diagnosis given by AI was 99% consistent with the diagnosis at the time, but from more than 300 cases, Watson found potentially additional genomic events.
According to a recent paper by The Oncologist in 2017, “The Molecular Oncology Committee with Cognitive Computing Authorization is likely to improve patient care by providing rapid, comprehensive data analysis methods combined with the latest clinical trials.â€
Reduce medical costs
The Kaiser Family FoundaTIon estimates that medical spending in the United States accounts for 18% of its GDP, which is disproportionate to its wealth. In fact, the per capita medical insurance expenditure in other developed countries is about half of that in the United States. AI can help reduce these costs. According to Accenture, AI can be used for management tasks, such as voice-to-text conversion, which can help medical institutions eliminate or reduce the need to write chart descriptions, prescriptions, and appointment checks.
For example, DeepMind, an AI company owned by Alphabet, last year used the AI ​​algorithm to read medical data in cooperation with the UK National Health Service. DeepMind has not yet made clinical decisions from the data, but as AI continues to learn from the data, it is expected to make recommendations for doctors in the future, which will save more time for healthcare professionals.
According to Accenture research, new workflow accessibility features like this can reduce doctors' work time by 17% and registered nurses by 51% of their working time. By improving the efficiency of the overall healthcare industry, AI is expected to create $150 billion in Medicare for the United States by 2026.
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