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Artificial Intelligence to Transform Healthcare as We Know It

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Artificial Intelligence to Transform Healthcare as We Know It

Let's see how AI is going to transform healthcare as we know it.

· AI Zone ·
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The 20th century has a new dictum: everything that can be automated will be automated. Artificial intelligence’s (AI) unstoppable power is reverberating across all industries. However, in healthcare, it can be truly life-changing. Technological experts promised that AI and machine learning would transform the healthcare industry with novel applications that could streamline workforce, reduce human error, improve drug recovery, and find new, effective drugs.

The concept of AI has been around floating since 1956, but it has made a significant improvement in the last decade. From drug development to clinical research and insurance, AI applications are disrupting the way the health sector works to improve patient outcomes and reduce patients’ bills. The total public and private investments in AI in the healthcare industry are absolutely stunning. According to Allied Market Research, the artificial intelligence in the healthcare market is projected to garner $22.79 billion by 2023 with CAGR of 48.7% from 2017 to 2023.

The rise in processing power of AI systems and its application for surgeries and screening coupled with the dearth of skilled healthcare professionals are the major drivers for the growth of AI in healthcare. In fact, Accenture called AI healthcare’s new nervous system. As per the company’s recently published study, AI in healthcare refers to the collection of multiple technologies that enable machine learning to sense, act, learn, and comprehend so they can administrate and perform clinical functions. With the gigantic power to improve cost and quality, AI in the healthcare market would multiply by the factor of 10 in the next five years.

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AI to Work With Humans

The shortage of healthcare professionals is the prime issue in most of the developing countries. The waiting times for doctors to check up on their patients could lead to poor health improvement. To improve diagnostics, Paragon Biosciences, the life science innovator, has recently launched Qlarity Imaging, a new company that aims at leveraging AI technology to improve medical outcomes and reduce costs.

Qlarity would advance a one-of-its-kind FDA-approved computer-based breast cancer diagnosis system in radiology that will offer advanced analytics, machine learning, and intuitive displays. According to the company, it has demonstrated effectiveness in interpreting cancerous and non-cancerous breast lesions to help radiologists. Its AI solution said to have shown a significant decrease of around 39% in missed breast cancers and around 20% overall improvement in diagnostic.

Jeff Aronin, the chairman and CEO of Paragon Biosciences, “By driving innovation across life science, our company is improving outcomes for patients with multiple medical conditions. So, we are happy that we could further develop AI-based diagnostic software for breast cancer MRIS.” He added that healthcare is entering into an exciting time where supercomputing and AI have made it possible to discover new drugs and improve diagnostics. Qlarity Imaging is expected to leverage Paragon’s capabilities and investments to further develop and deploy its computer-based diagnosis system along with expanding AI diagnostic tools.

Launch of New AI Centers

Cleveland Clinic, American academic medical center, announced to launch a new center for AI that would collaborate and communicate between physicians, researchers, and data scientists and gain traction across the health system. The aim is to boost the research on several clinical use cases where machine learning, deep learning, and AI would work together. The project would seek new and innovative AI applications for disease prediction, diagnostics, and treatment planning.

Even now, researchers at the center are working on developing new machine learning and AI-based tools for more precise clinical decision support, predictions of length and risks, and quality improvement. Moreover, the center has other initiatives focused on oncology that explore how AI can enable personalized outcome prediction.

AI for Simplifying Hospital Workflow

The AI has the potential to analyze information such as medical records and patients' medical history. Data management is the most attractive feature of AI, and if coupled with digital automation and robotics, the healthcare centers could provide a faster and more consistent diagnosis. In addition, AI could accurately analyze tests, CT scans, X-rays, and other mundane tasks that consume doctors’ precious time. Cardiology and radiology are two disciplines that produce the humongous amount of data and its analysis becomes overwhelming. With the help of AI, healthcare professionals would have to look at those cases that are too complicated and where human supervision is a must.

Another the most exciting application of AI is the digital nurse, Molly. A startup, Sense.ly, has launched Molly that helps people monitor patients' conditions and follows up with treatment between doctor visits. The program uses machine learning to help patients suffering from chronic illness. Apart from Molly, a few years ago, Boston Children’s Hospital had launched an Amazon Alexa app that offered basic health care information and advice for patients as well as children. Moreover, the app was programmed to answer asked questions regarding medications and whether the symptoms require a doctor’s visit or not.

Although people still have bitterness in their mind and fear that AI will soon take over the jobs of doctors, experts believe that it is quite baseless and based on sci-fic movies than reality. The fact is AI offers innumerable opportunities in the medical field and has protentional to take the current healthcare system far beyond our imagination.

Topics:
artificial intelligence in healthcare ,artificial intelligence ,healthcare ,ai in healthcare ,ai working with humans ,ai doctors ,robot doctors ,ai centers ,hospital workflow

Opinions expressed by DZone contributors are their own.

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