AI is one of the promising revolutions in the teleradiology sector. In the last ten years, the numbers on AI in radiology rose from 100 to 150 research publications to 700 to 800 per year. The implementation of AI is higher in MRI and CT systems when compared to other imaging modalities.
The Opportunities
AI is mostly incorporated with neuroradiology on the basis of applications. Many players in this field have enhanced their contributions in the field of artificial intelligence.
AI can help to set up an inbuilt mechanism that prioritizes cases based on a protocol condition. For instance, stroke and trauma-related cases can be given high priority by assigning to the work lists of the radiologist. This way, numerous lives can be protected.
The Challenges
There is no denying that teleradiology shares the clinical images for healthcare delivery. But, cybersecurity steps to safeguard the health information of the patients are yet to be applied. There are legal and ethical obligations for healthcare staff to maintain privacy and also to keep the patient’s data confidential as it may have some intimate details about a patient. There could be major data loss that may lead to delay in treatment which is the biggest challenge for the development of this market.