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Surgical robots, new medicines and better care: 32 examples of AI in healthcare

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Artificial intelligence simplifies the lives of patients, doctors and hospital administrators by performing tasks that are typically done by humans, but in less time and at a fraction of the cost. One of the world's highest-growth industries, the AI sector was valued at about $600 million in 2014 and is projected to reach a $150 billion by 2026. Whether it's used to find new links between genetic codes or to drive surgery-assisting robots, artificial intelligence is reinventing -- and reinvigorating -- modern healthcare through machines that can predict, comprehend, learn and act. Check out these 32 examples of AI in healthcare. In 2015, misdiagnosing illness and medical error accounted for 10% of all US deaths. In light of that, the promise of improving the diagnostic process is one of AI's most exciting healthcare applications.


The Impact of Artificial Intelligence in Healthcare

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According to PricewaterhouseCoopers, "chronic diseases and conditions are on the rise worldwide." When infectious diseases like SARS and Ebola emerged, there was a rapid, global spread. Given the significant increase in global mobility, outbreaks must be dealt with quickly to minimize the number of people who may be infected. Although there have been significant advances in the control of common communicable diseases, presently, some of the most common infections like tuberculosis, malaria, and HIV still do not have effective vaccines. On a positive note, the past few years has also seen major progress in the diagnosis, management and prevention of certain cancers like cervix and breast cancer and childhood leukemia.


Artificial Intelligence in Healthcare - A Comprehensive Account - Maruti Techlabs

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To say that the role of Artificial Intelligence in Healthcare is intriguing, would be an understatement. AI and Machine Learning can bring about changes that have a substantial impact on healthcare processes and administration & while there is a lot we have to overcome to reach the stage of AI-dependent healthcare, there is sufficient potential in the technology today to drive governments, healthcare institutions, and providers to invest in AI-powered solutions. A study by Accenture has predicted that growth in the AI healthcare space is expected to touch $6.6 billion by 2021 with a CAGR of 40%. As on today, Artificial Intelligence and Machine Learning are well and truly poised to make the work of healthcare providers more logical & streamlined than repetitive. The technology is helping shape personalized healthcare services while significantly reducing the time to look for information that is critical to decision making and facilitating better care for patients.


Decoding the Future Trajectory of Healthcare with AI - ReadWrite

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Artificial Intelligence (AI) is getting increasingly sophisticated day by day in its application, with enhanced efficiency and speed at a lower cost. Every single sector has been reaping benefits from AI in recent times. The Healthcare industry is no exception. Here is decoding the future trajectory of healthcare with AI. The impact of artificial intelligence in the healthcare industry through machine learning (ML) and natural language processing (NLP) is transforming care delivery.


AI has arrived - PharmaTimes Magazine October 2018

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Artificial intelligence is poised to change the pharmaceutical and healthcare industries as it looks to streamline, speed-up and improve overall efficiency. It might still be early days but it's a bandwagon that organisations are quickly jumping on board. According to a CB Insights report, about 86% of healthcare organisations, life science companies and med tech firms were using artificial intelligence technology in 2016. Big pharma names announcing deals and applications include Bayer, J&J, Merck, Sanofi, Genentech and Pfizer. Meanwhile, more than 50% of healthcare industry executives anticipate broad-scale adoption of the technology by 2025, a TechEmergence study recently revealed, with nearly half of the respondents noting that chronic conditions will be the initial target.