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How AI is enhancing medical diagnostics

Bio Spectrum

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BioSpectrum India June 2025

India's medical diagnostics sector is undergoing a transformative shift, fuelled by the power of Artificial Intelligence (AI). According to a report by Research and Markets, the AI-based Medical Diagnostics Market in India was valued at $12.87 million in 2024 and is projected to soar to $44.87 million by 2030, growing at an impressive CAGR of 23.1 per cent.

- Vrushti Kothari

How AI is enhancing medical diagnostics

However, the rapid adoption of AI technologies in diagnostics is probably more focused on early detection of diseases such as cancer, respiratory diseases, diabetes, and cardiovascular diseases, among others. Sensing this bend, the industry has now started deploying AI to detect unexplored areas such as ophthalmology, dermatology, trichology, in vitro fertilisation, to name a few. Let's find out more about the potential that lies in the hands of AI in medical diagnostics.

AI is rapidly transforming healthcare, particularly in diagnostics and imaging across the globe. The industry is continuously developing solutions in the form of new apps and devices using AI to ease out the burden on the healthcare setting. As a result, these solutions are improving diagnostic accuracy and enabling faster treatment decisions for conditions such as cancer, tuberculosis, diabetes, cardiovascular diseases etc.

With India witnessing a rising burden of these diseases, coupled with a shortage of skilled healthcare professionals, AI-driven diagnostic solutions are emerging as a transformative force. By reducing diagnostic turnaround times, increasing accuracy, and enabling remote healthcare access, AI is playing a pivotal role in addressing the growing healthcare demand and disease burden, particularly in urban areas where non-communicable diseases (NCDs) are more prevalent.

However, challenges persist in terms of high implementation costs, the lack of standardised AI regulations, a limited skilled workforce and concerns over data privacy and patient confidentiality. Furthermore, limited adoption of AI in rural healthcare facilities remains a significant barrier to widespread deployment in India.

Despite these challenges, many new areas such as ophthalmology, dermatology, trichology, in vitro fertilisation, etc. are being touched upon by the industry where the use of AI can offer timely diagnosis and effective treatment plans.

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