Be first to read the latest tech news, Industry Leader's Insights, and CIO interviews of medium and large enterprises exclusively from CIO Advisor APAC
Continuous technological developments in healthcare have enhanced the entire experience for both patients and medical professionals improving operational efficiency and standards in patient care. Machine learning helps physicians analyze patient’s data and loop it back in real time to make better clinical decisions.
Machine learning could significantly reduce the time and effort required to review a patient’s past clinical data and identify indicators that could impact a patient’s care and outcome. But the point at issue is the accuracy of data as the cyber attacks or security breaches might affect this sensitive data. However, there is insufficient data about condition bias which might affect data integrity. Machine learning, with the predictive analytical tool, can produce results that are more accurate; this can be achieved by training and customizing the software over time and respond to exact values accordingly.
By using big data, patients themselves will be able to engage in early detection of potential illnesses and intervene more effectively in the management of their health and reduce the need to visit the doctor. Big data, delivered through wearable tech and integrated health records will make it possible for them to reduce costly expenditures on drugs and hospital care. Chatbots are also making their way in the healthcare field, to book doctor appointments and monitor health status by giving more information at fingertips.
Prognos is a New York-based startup whose primary goal is to eliminate diseases by using artificial intelligence to predict disease and drive decisions earlier in healthcare; the company raised funds worth $20,500,000 last year. IDx-DR is an AI-based software program that checks eye diseases by examining retina photos, and the software identifies the correct disease in 87 percent cases. According to an IDC report, by 2020, one out of four hospitals with at least a 200-bed capacity would deploy robotics to handle time-consuming tasks, to reduce error that enables business sustainability. With a CAGR of 42.6 percent during 2018-2023, the machine learning market value is expected to reach $23.46 billion by2023. Though there are some challenges with the advancement in AI and NLP technologies, the world is much closer to data-driven healthcare.