India Artificial Intelligence (AI) in Diagnostics Market Report 2022 to 2030

India Artificial Intelligence (AI) in Diagnostics Market Analysis

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India's 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. The market will be driven by the rising number of startups in AI diagnostic technology and government initiatives. The market is segmented by component & by diagnosis. Some of the major players include IBM Watson Health, Siemens Healthineers & Qure AI.

ID: IN10INDH002 CATEGORY: Digital Health GEOGRAPHY: India AUTHOR: Vidhi Upadhyay

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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 diagnosis. 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.

India artificial intelligence in diagnostics market analysis report 2022 to 2030

Market Dynamics

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.

Market Restraints

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 inadequate. 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

Key Players

IBM Watson Health
Siemens Healthineers
Philips Healthcare
GE Healthcare
Google Health
AliveCor, Inc.
Riverain Technologies
Qure AI (IND)
Niramai (IND)
Predible Health (IND)

Notable Deals

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.

1. Executive Summary
1.1 Digital Health Overview
1.2 Global Scenario
1.3 Country Overview
1.4 Healthcare Scenario in Country
1.5 Digital Health Policy in Country
1.6 Recent Developments in the Country

2. Market Size and Forecasting
2.1 Market Size (With Excel and Methodology)
2.2 Market Segmentation (Check all Segments in Segmentation Section)

3. Market Dynamics
3.1 Market Drivers
3.2 Market Restraints

4. Competitive Landscape
4.1 Major Market Share

4.2 Key Company Profile (Check all Companies in the Summary Section)

4.2.1 Company
4.2.1.1 Overview
4.2.1.2 Product Applications and Services
4.2.1.3 Recent Developments
4.2.1.4 Partnerships Ecosystem
4.2.1.5 Financials (Based on Availability)

5. Reimbursement Scenario
5.1 Reimbursement Regulation
5.2 Reimbursement Process for Diagnosis
5.3 Reimbursement Process for Treatment

6. Methodology and Scope

India Artificial Intelligence (AI) in Diagnostics Market Segmentation

By Component Outlook Type (Revenue, USD Billion):
- Software
- Hardware
- Services

By Diagnosis Outlook Type (Revenue, USD Billion):
- Cardiology
- Oncology
- Pathology
- Radiology
- Chest and Lung
- Neurology
- Others

Methodology for Database Creation

Our database offers a comprehensive list of healthcare centers, meticulously curated to provide detailed information on a wide range of specialties and services. It includes top-tier hospitals, clinics, and diagnostic facilities across 30 countries and 24 specialties, ensuring users can find the healthcare services they need.

Additionally, we provide a comprehensive list of Key Opinion Leaders (KOLs) based on your requirements. Our curated list captures various crucial aspects of the KOLs, offering more than just general information. Whether you're looking to boost brand awareness, drive engagement, or launch a new product, our extensive list of KOLs ensures you have the right experts by your side. Covering 30 countries and 36 specialties, our database guarantees access to the best KOLs in the healthcare industry, supporting strategic decisions and enhancing your initiatives.

How Do We Get It?

Our database is created and maintained through a combination of secondary and primary research methodologies.

1. Secondary Research

With many years of experience in the healthcare field, we have our own rich proprietary data from various past projects. This historical data serves as the foundation for our database. Our continuous process of gathering data involves:

Analyzing historical proprietary data collected from multiple projects.
Regularly updating our existing data sets with new findings and trends.
Ensuring data consistency and accuracy through rigorous validation processes.

With extensive experience in the field, we have developed a proprietary GenAI-based technology that is uniquely tailored to our organization. This advanced technology enables us to scan a wide array of relevant information sources across the internet. Our data-gathering process includes:

Searching through academic conferences, published research, citations, and social media platforms
Collecting and compiling diverse data to build a comprehensive and detailed database
Continuously updating our database with new information to ensure its relevance and accuracy

2. Primary Research

To complement and validate our secondary data, we engage in primary research through local tie-ups and partnerships. This process involves:

Collaborating with local healthcare providers, hospitals, and clinics to gather real-time data.
Conducting surveys, interviews, and field studies to collect fresh data directly from the source.
Continuously refreshing our database to ensure that the information remains current and reliable.
Validating secondary data through cross-referencing with primary data to ensure accuracy and relevance.

Combining Secondary and Primary Research

By integrating both secondary and primary research methodologies, we ensure that our database is comprehensive, accurate, and up-to-date. The combined process involves:

Merging historical data from secondary research with real-time data from primary research.
Conducting thorough data validation and cleansing to remove inconsistencies and errors.
Organizing data into a structured format that is easily accessible and usable for various applications.
Continuously monitoring and updating the database to reflect the latest developments and trends in the healthcare field.

Through this meticulous process, we create a final database tailored to each region and domain within the healthcare industry. This approach ensures that our clients receive reliable and relevant data, empowering them to make informed decisions and drive innovation in their respective fields.