Global AI in Medical Diagnostics Market to Be Driven by Demand for Image Recognition in Radiology

These are the latest findings of TMR Research (San Francisco, CA, USA).

AI has shown transformative potential in medical and healthcare industry. In particular, the effects of AI penetration in medical diagnostics have expanded the canvas for offering high-quality patient care. Early disease detection is one of the key applications where AI players are exploring game-changing potential and are zealously investing in deploying AI in radiology to complement conventional procedures. Image recognition is perhaps the most compelling consumer proposition in the AI in medical diagnostics market. Algorithms have been learning and unlearning and relearning signs of diseases in millions of images clinicians extract from the target population. A key trend has been outsourcing these to developing economies to save cost.

There has been a flurry of activities in deep learning algorithms to advance access to quality diagnostics and at a low cost. This can be lifesaving in the case of chronic conditions that may become fatal if not diagnosed early. Patients who are at the receiving end are those with significant cardiovascular diseases risks. Further, another factor that is driving research in AI in medical diagnostics market is the need for improving the accuracy of diagnosis, either through single or several images. The internet of medical things is making vast strides, as evident in the proliferation of AI-based apps. AI companies are keen on bridging the vast gap between demand and supply of radiologists while simultaneously reducing the cost of radiological examinations. On the whole, the key clinical proposition of AI in healthcare is the use of AI apps in the detection of diseases and advance patient-centered care.

Several recent research and development projects, including those pioneered by stalwart technology companies, show rising huge dollar inflows into the AI in medical diagnostics market such as the advent of AI-based apps that improve breast cancer detection accuracy. The prospects of AI-driven software in cancer detection present vast possibilities. Another area that holds strong prospects is the use of AI for detecting skin problems from the images of skin lesions. Such developments are expected to open up new avenues for various industry stakeholders in the AI in medical diagnostics market. Companies are also intensifying R&D efforts for leveraging the potential of AI in multiple retinal diseases.

Geographically, North America is a highly lucrative region, fuelled largely by increasing R&D in developing AI-apps for reducing the burden and prevalence of various chronic diseases. The North American market is expected to witness vast revenue streams from the efforts by players in the ecosystem to bring AI and deep learning systems from the bench to the bedside, notably in diseases that are more prevalent in countries such as the US. Asia Pacific is also a promising regional market for AI in medical diagnostics and is anticipated to make rapid strides in the near future, fueled by the growing penetration of AI in healthcare.

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