Artificial Intelligence - Tailwind of the Digital Success of Radiology
Let’s hear it more precisely from Dr Arjun Kalyanpur, Chief Radiologist and Founder/ CEO of Teleradiology Solutions in a thorough interaction with Indranil Chakraborty, Assistant Editor at Siliconindia. Dr Arjun succinctly portrays how AI plays a compelling role in the digital shift of Radiology and how humans and technology can come together to add value to patient care.
1. Shed some light on how AI scales Radiology.
Over the last few years, the impact of artificial intelligence and machine learning has been growing exponentially. Like any other field, artificial intelligence made its way into radiology. It is a valuable tool that offers vast potential to the healthcare industry at a time of radiologist shortage by using deep learning to capture electronically the expertise of radiologists and clinicians. From bridging the gap between the demands of ever-mounting, extremely complex data and the relatively inadequate number of radiologists, to simplifying data interpretation and analysis AI improves the diagnostic process, thereby fostering patient safety. Some of the benefits that AI delivers in Radiology include.
● Detection and Classification: Deep learning-based algorithms can detect abnormalities such as bleeding in the brain on CT scans or early breast cancer on mammography. In the case of algorithms developed by our organization Telerad Tech, the Neural assist algorithm can also quantify the size of the bleed and localize it. Our MammoAssist algorithm provides a BIRADS score that provides a risk stratification for the probability of breast cancer. These algorithms function at a high level of accuracy and speed.
● Detection of complications – In the case of the Neural Assist algorithm, the algorithm also detects complications of the bleed, such as brain swelling which are predictors of poor outcome and need aggressive intervention.
● Triage: In the emergency setting the process of triage, in which patients are quickly screened and more critical patients are given attention on priority, is of importance. Similarly in a situation where the volume of cases is piling up for the radiologist to interpret, an AI algorithm which identifies critical abnormalities and alerts the radiologist of great value. Our NeuraAssist algorithm provides an instant alert that allows the emergency radiologist to prioritize the positive cases and give them primary attention to improve patient outcomes.
2. What does AI hold for the Future of Radiologists?
Undoubtedly there is hype around AI radiology today that it is soon going to replace radiologists in healthcare, however, this is not true. The human touch is critical in both the final analysis and patient care Hence, AI will not replace radiologists, but radiologists will start using AI soon, to help improve both their accuracy and their productivity. This is why the healthcare world should welcome it with open arms and embrace it rather than feel threatened by it or neglect it.
3. Brief us on why Radiology still remains the most demanded specialty post-MBBS.
Radiology is a key part of healthcare, given that all other specialties are ultimately dependent on it, and is highly focused on the use of technology. It is a specialty where technology and human intelligence go hand-in-hand to promote patient care, therefore, there is an interesting opportunity for young doctors to be a part of this amazing engagement. The radiology sector provides a large number of job openings, holds opportunities for entrepreneurship and is financially rewarding, thereby attracting more youth under it.
4. Enlighten us about AI aiding in the diagnosis of breast cancer.
Among all types of cancer, breast cancer is now the most common type of cancer occurring in Indian women. Due to a lack of awareness about this disease, the majority of patients present very late and often at a stage where the disease has already progressed throughout the body. Technologies such as full-field digital mammography and digital breast tomosynthesis exist which aid in the early detection of breast cancer. However, these are complex and time-consuming to interpret. AI algorithms such as our MammoAssist algorithm detect and display suspicious features in the image, and predict the likelihood of malignancy at an early and curable stage. In simple words, it supports the institution of treatment at an early stage that saves lives.
5. Teleradiology: The Digital Healthcare Revolution
Digital health solutions are in focus today and their usage rapidly escalated during the Covid and post-Covid scenarios. One such revolutionary digital solution is Teleradiology, which has tremendously enhanced service efficiency throughout the pandemic. It utilizes telecommunication networks in order to transmit patient scan images, and other radiological information to ensure prompt radiologic interpretation, which is of great benefit in acute conditions. Additionally, by placing radiologists in different time zones, it addresses the overnight workloads and converts night to day work, deals with emergency cases, solves radiologist shortage issues, and provides remote consultation by sub-specialized radiologists.