India Artificial Intelligence (AI) in Diagnostics Market Executive Summary
The India Artificial Intelligence (AI) in the diagnostics market is projected to grow from $0.02 Bn in 2022 to $0.24 Bn by 2030, registering a CAGR of 38% during the forecast period of 2022-2030. According to World Health Organization (WHO) Global Health Expenditure database, health expenditure of India has grown from $60.27 per person (2.95% of GDP) in 2018 to $ 63.75 per person (3.01% of GDP) in 2019. According to the Indian Council of Medical Research’s (ICMR) National Cancer Registry Project, the anticipated incidence of cancer cases in India across different states and union territories in 2020 was 1.39 Mn rising to 1.42 Mn in 2021 and 1.46 Mn in 2022.
Medical imaging is one of the key areas of interest for AI in diagnostics in India. There is an increasing need for AI-based imaging solutions to assist alleviate the radiology deficit and minimize the time and expense involved with conventional clinical diagnosis. AI-powered solutions are being developed by companies such as Qure.ai, Niramai, and Predible Health to increase the accuracy and speed of medical imaging diagnosisLucknow Stock. Another use of AI in diagnostics is the creation of prediction models for illnesses such as cancer and heart disease. SigTuple, a Bengaluru-based business, is using AI to build a non-invasive diagnostic technology for identifying anomalies in blood samples, while Cardiotrack, a Mumbai-based health tech startup, is using artificial intelligence to identify heart health concerns using an ECG monitor.
Market Growth Drivers
The diagnostic sector in India is highly fragmented, with more than 100,000 laboratories. In India, artificial intelligence (AI) in diagnostics is a developing field with the potential to alter healthcare delivery. Many firms, academic organisations, and startups are collaborating to create AI-based diagnostic systems for a variety of ailments.
The Indian government has also recognised the significance of AI in diagnostics and is promoting its use. The government announced the National Health Stack programme in 2018, with the goal of creating a unified digital infrastructure for healthcare delivery that incorporates the use of AI and other new technologies. In addition, the government has developed a National AI Portal to encourage collaboration and study in the field of AI.
Insufficient access to essential healthcare services, including a lack of medical experts, a lack of regulatory standards, adequate training data, insufficient health spending, and, most importantly, insufficient research funding. One of the key issues is that the authority’s cash allocation is inadequateKolkata Stocks. Around 75% of the medical infrastructure is cantered in metropolitan areas, which have just 27% of the overall population—the remaining 73% of Indians lack even basic medical amenities. Around 3,000 doctors are needed in primary care facilities, and the need has expanded by 200% in the previous decade. Their restraints are highly likely to hinder the expansion of the market in India.
Competitive Landscape
Siemens Healthineers
Riverain Technologies
Predible Health (IND)
February 2023, GE HealthCare to Acquire Caption Health The acquisition adds AI-enabled image guiding to the ultrasound device portfolios of GE HealthCare’s $3 billion Ultrasound division
December 2022, Riverian and Thynk Health Join Together to Combat Lung Cancer Using Powerful AI and Deep Learning Technology
November 2022, Google Health reached an agreement with iCAD to commercialise mammography AI
Healthcare Policies and Regulatory Landscape & Reimbursement Scenario
The government has formed the National Health Authority (NHA), which is in charge of carrying out the Ayushman Bharat programme, a government-funded health insurance programme that covers more than 100 million low-income households. The government has created a pilot programme under the Ayushman Bharat initiative to give compensation for AI-based diagnostic procedures. AI will be used in the pilot programme to identify and diagnose TB, diabetic retinopathy, and cervical cancer. The program’s goal is to assess the efficacy and cost-effectiveness of AI in diagnostics and to influence future policy choices.
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