AI technology in healthcare advances surgical, clinical support

Healthcare has long considered technology as essential in improving the treatment and care of patients. With AI ushering in what's said to be the fourth industrial revolution, many hospitals are gearing up for new AI-based applications that will further improve patient outcomes, increase physician productivity and reduce errors.

Based on several studies, AI-based applications can potentially save the U.S. healthcare industry $150 billion annually by 2026. As AI technology in healthcare continues to gain wider acceptance, several areas are predicted to experience the most success and make the greatest impact.

Virtual nurses inside and outside the hospital. Hospitals find it challenging to recruit nurses in several parts of the U.S., and in some rural areas, the nursing shortage is affecting patient care. AI has shown substantial value in helping solve this problem by using natural language processing and machine learning in virtual assistants. Many of us use virtual assistants in our homes and on our devices, and more vendors are focusing on AI technology in healthcare to engage patients and support their needs through 24/7 conversation.

Robot-assisted surgery. AI will play a key role in assisting during surgeries and office surgical procedures. Robots have made significant strides in other industries, taking over jobs and tasks that are too repetitive or deemed unsafe for humans. They have also delivered automation and helped reduce human error. A popular example of AI in healthcare is robot-assisted surgery with the da Vinci surgical robot, which is still controlled by trained surgeons and helps perform minimally invasive surgeries. Cardiac, gynecological, thoracic and other types of surgeries have all benefitted from these robots.

Medical imaging analysis and disease detection. AI technology in healthcare can provide deep analysis of medical images and early detection of potential health issues by using computer vision systems combined with machine learning to analyze MRIs, CT scans and X-rays. Traditionally, a human would review medical images and at times find it difficult to detect certain abnormalities with the naked eye. AI can learn from thousands of scans and diagnoses using algorithms to detect and label abnormalities, giving hospitals and physicians an extra layer of "expertise" to help determine any issues that may have been overlooked or undetected by humans.

Clinical screening decisions. Patients being treated or seen by a physician are likely to have their data in a digital format. An AI platform can screen this data and give feedback to physicians, such as potential treatment options and possible diagnoses. There have been a number of real cases where AI technology in healthcare screens and detects patients with diabetes and heart problems. For example, a company called IDx markets to optometrists, who can then upload images of retina scans to the IDx cloud for image analysis and immediate feedback on diabetic retinopathy.

AI can learn from thousands of scans and diagnoses using algorithms to detect and label abnormalities.

Feedback for patient-generated data. In recent months, there have been a number of news articles highlighting how the Apple Watch has helped some owners prevent serious health issues by monitoring heart rate and notifying the user when abnormal heart rhythms are detected. This type of analysis of data collected by wearables is likely to expand beyond heart monitors and into other fitness and medical devices. By applying some level of AI to the data in real time, patients can receive valuable and perhaps live-saving feedback.

Although AI technology in healthcare continues to improve and mature, healthcare professionals may still be hesitant in trusting computer-based software to make clinical decisions for them. But the technology has shown great potential in recent years and, at the very least, can be a powerful ally to healthcare providers.