Current Trends and Future Possibilities of AI in Medicine
healthcaretechoutlook

Current Trends and Future Possibilities of AI in Medicine

By Healthcare Tech Outlook | Friday, June 07, 2019

AI in MedicineFREMONT, CA: In recent years, Artificial intelligence (AI) in medicine and healthcare has been mainly, a hot topic. In medicine, AI relies on the power of computers to sift through and make sense of reams of electronic data about patients—including their age, medical history, health status, test results, medical images, DNA sequences, and many other sources. AI excels at the identification of patterns in these reams of data, that also at speed beyond human capacity. The promise is that this technology can be leveraged to help doctors and patients make better healthcare decisions. The uses of AI in healthcare do not stop at understanding human commands and knowing what type of resolution is needed.

One of the areas of AI that is beginning to gain momentum is in the field of customer service, and healthcare bots are to be available. A bot is an AI application patients can interact with through a chat window on a website or via telephone to receive assistance when demanded. It can be used in situations, including scheduling follow-up appointments with doctors online. Other instances include a bot helping patients with their medication or medical billing needs. These uses of AI in healthcare improve customer service and offer 24/7 assistance for basic requests, thereby reducing the overall administrative costs for hospitals.

Another most valuable use of AI in healthcare is in radiology. AI can assist in the diagnostic processes by analyzing many of the medical images such as MRIs, X-rays, and CT scans and facilitating with feedback on what it can detect that the naked eye may miss. Developing pharmaceuticals through clinical trials is a time and cost consuming effort.  Making this process faster and cheaper could change the world. A program powered by AI can scan existing medicines that could be redesigned to fight diseases.

To help lessen the time spent by health professionals on documentation, natural language processing (NLP) can extract that data and enter the information into the EHR. NLP that has been introduced recently around the analysis of clinical documentation. Advanced NLP systems can sort through the existing content of the charts and highlight the relevant data for the clinical practitioners.

By adopting applications of AI, healthcare institutions can deliver on several key objectives, including enhancing patient outcomes and increasing staff efficiency. Over time, more innovations in AI will drive its adoption further in the sector.

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