The global shortage of radiologists presents a significant and widespread challenge, affecting both developed and developing nations. Countries like Japan, the UK, and India, with a population of 1.3 billion and only 15,000 radiologists, grapple with delayed, costly, and often inaccessible medical imaging services. Addressing this crisis necessitates the integration of technology, particularly Artificial Intelligence (AI), a transformation that is increasingly becoming a vital component of healthcare worldwide.
AI is no longer considered a luxury but rather a critical necessity in the healthcare sector. In India, several companies are at the forefront of integrating AI into clinical practice, making radiology more accessible, efficient, and accurate. These companies have successfully implemented AI solutions, thereby enhancing radiology workflows and improving patient outcomes.
Challenging Volumes
While traditional Picture Archiving and Communication Systems (PACS) have effectively managed medical imaging information, the growing volume of these images presents a challenge. Innovative AI platforms are revolutionising PACS by optimising radiology workflows seamlessly. These platforms combine cutting-edge AI technology and Smart Reporting to enhance productivity and quality gains. As vendor-neutral platforms, they easily integrate third-party AI models into existing workflows, thus streamlining processes and improving efficiency.
There are certain AI platforms that acts as a virtual assistant, intelligently prioritising worklists and efficiently sorting incoming scans. These platforms highlight critical cases and pinpoints abnormalities with precision, going beyond speed to meticulously scrutinise each image. This acceleration in diagnoses holds the potential to improve patient outcomes significantly. These platforms’ benefits extend further with click-generated reports, saving radiologists’ time, and fostering seamless collaboration between technicians, radiologists, and referring physicians.
AI-powered solutions are also addressing specific challenges within radiology, such as the interpretation of chest X-rays. With 3.5 billion chest X-rays performed annually worldwide, timely and accurate interpretation is essential. AI solutions intelligently categorise X-rays into " scans with low suspicion" and "scans with high-suspicion" categories, allowing radiologists to prioritise critical cases for faster diagnoses while junior radiologists or the platform itself can handle the scans with low suspicion, boosting efficiency by 30-50%.
This streamlined workflow not only saves time but also improves patient outcomes through faster diagnoses, enhances accuracy with AI acting as a second pair of eyes, and reduces costs for healthcare systems by optimising resource allocation.
Screening Process Automation
Additionally, AI tools play a crucial role in screening for lung pathologies, such as Tuberculosis (TB) and Pneumonia. These tools automate the screening process, enabling quick and accurate identification of abnormalities. They can be used in various settings, including hospitals, health centres, and even remote areas with limited access to experts, thus facilitating widespread screening and early detection of diseases.
For instance, there are even groundbreaking solutions available in the market that triages individuals with suspected pathologies within a minute. The software analyses X-rays within seconds, allowing healthcare workers to make quick diagnoses and initiate treatment immediately. Hence, these solutions not only improve patient outcomes but also reduces costs associated with TB, marking a significant advancement in efficient and widespread TB detection and management.
Remote Access
As the radiology AI market is estimated to be a billion-dollar industry today, with expectations to reach $30 billion by 2030, AI startups are driving innovation in the field, transforming challenges into opportunities for improvement. Furthermore, AI has empowered radiologists to work remotely, facilitating global collaboration and improving access to radiology services, even in regions with limited resources.
Today, a radiologist sitting in India can facilitate reporting not just in the remotest part of the country but also to other countries like the US and even countries with no radiologists, such as African countries. This technology at their fingertips has made this global collaboration possible, showcasing the transformative impact of AI in the field of radiology.
In conclusion, AI solutions are playing a pivotal role in addressing the global radiologist shortage and improving healthcare outcomes worldwide. By leveraging AI technology, healthcare systems can enhance efficiency, accuracy, and accessibility in radiology, ultimately benefiting patients and healthcare providers alike.
—The author, Dr. Amit Kharat, is CEO & Co-founder of DeepTek.ai, an AI-led medtech venture in the radiology and medical imaging space. The views expressed are personal.
(Edited by : C H Unnikrishnan)
First Published: Mar 13, 2024 2:20 PM IST
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