Artificial Intelligence (AI) is becoming an important part of India’s health ecosystem, helping transform healthcare delivery. From early disease detection to personalized treatment plans, AI is improving the accuracy and efficiency of medical services. By analyzing large sets of health data, AI tools can help doctors make better decisions and provide more targeted care. AI-powered applications also make healthcare more accessible, especially in remote areas where medical professionals are scarce. As AI continues to grow, it is expected to play an even bigger role in enhancing the quality and reach of healthcare in India.
Tags: GS – 2, Health- Government Policies & Interventions, GS – 4- Ethics
Context:
- India cannot jump into AI-driven health care without first addressing the foundational issues within its health system.
- AI technologies promise to increase efficiency, improve access to medical expertise, and potentially revolutionise healthcare delivery in a country.
Significance of AI in Healthcare:
- Revolutionising Diagnostics: A 2020 study in Nature showed AI reduced false-positive and false-negative breast cancer detections by 1.2% and 2.7%, respectively.
- Personalised Treatment Plans: IBM Watson Oncology, used in over 230 hospitals, assists in crafting personalised cancer treatments, improving patient outcomes and resource use.
- Drug Discovery and Development: In 2020, Insilico Medicine used AI to design a fibrosis drug candidate in just 46 days, significantly faster than traditional methods.
- Enhancing Clinical Workflows: Reducing administrative tasks like transcribing doctor-patient conversations, updating health records and optimising patient flow and resource allocation in hospitals.
- Remote Monitoring and Telemedicine: During COVID-19, platforms like Babylon Health used WHO’s AI, “Sarah to triage patients, provides health tips in eight languages but does not offer medical advice.
- Enhancing Medical Education and Training: Companies like FundamentalVR offer haptic VR systems for surgical practice. AI-driven adaptive learning tailors curricula to students, enhancing training efficiency.
Major Challenges of AI in Healthcare in India
- Data Challenges: Leads to inconsistent data collection and lacks provisions for integrating electronic health records (EHRs) with issues like data quality, standardisation, and interoperability further complicate AI model training.
- Digital Divide: With 45% of the population lacking internet access, rural areas lag in digital infrastructure, hindering equitable, disproportionately benefit urban populations, widening healthcare disparities.
- Regulatory Hurdles: The proposed Digital Information Security in Healthcare Act (DISHA) is still unenacted, creating uncertainty regarding AI validation, liability, and patient data protection.
- Ethical and Cultural Considerations: AI trained on Western data may not suit Indian populations, and cultural sensitivities complicate data sharing.
- Cost and Resource Allocation: Ranging from USD 20,000 to USD 1,000,000, With healthcare spending only 1.8% of GDP in 2020-21, funding is a challenge.
- Language and Localization: With 22 official languages and numerous dialects, language barriers can cause misdiagnosis, miscommunication, and reduce AI’s effectiveness in healthcare.
How India Can Effectively Implement AI in Healthcare
- Strengthen National Health Resources Database: National Health Resources Repository (NHRR) and the National Digital Health Mission help build a robust AI Healthcare Model similar to Estonia’s e-Health system, covering 95% of its population’s health data.
- Develop India-Specific AI Models: Initiatives like IIT-Delhi’s AI-based detectors for diseases could guide the development of India-specific solutions.
- Tiered AI Implementation Strategy: Use advanced AI in urban tertiary hospitals, robust AI tools in rural areas for basic screenings and telemedicine with limited connectivity. The Aarogya Setu app shows the potential for mobile health tech.
- Establish a Regulatory Sandbox for AI: Modelled after the RBI’s fintech sandbox, this approach could allow innovation while ensuring regulatory oversight and the ICMR could oversee this initiative.
- Integrate AI in Medical Education: Partner with online platforms to offer certified AI courses to healthcare professionals, following successful examples like Stanford’s AI in Healthcare course.
- Establish Ethical Guidelines: A dedicated AI Ethics Committee under the Ministry of Health could ensure ethical use, drawing inspiration from the EU’s guidelines addressing data privacy, algorithmic bias, and AI’s role in clinical decision-making.
- Create AI-Ready Healthcare Infrastructure: Leverage existing government schemes like the National Rural Health Mission, and replicate successful solar-powered health centres for digital infrastructure.
- Launch Public Awareness Campaigns: Focus on explaining the benefits and limitations of AI through media channels, modelled on the successful Pulse Polio campaign, using grassroots mobilisation and celebrity endorsements to educate the public.
UPSC Civil Services Examination, Previous Year Question (PYQ)
Prelims:
Q1. With the present state of development, Artificial Intelligence can effectively do which of the following? (2020)
- Bring down electricity consumption in industrial units
- Create meaningful short stories and songs
- Disease diagnosis
- Text-to-Speech Conversion
- Wireless transmission of electrical energy
Select the correct answer using the code given below:
- 1, 2, 3 and 5 only
- 1, 3 and 4 only
- 2, 4 and 5 only
- 1, 2, 3, 4 and 5
Ans: (b)
Q2. Consider the following pairs: (2018)
Terms sometimes seen in news Context/Topic
- Belle II experiment Artificial Intelligence
- Blockchain technology Digital/Cryptocurrency
- CRISPR–Cas9 Particle Physics
Which of the pairs given above is/are correctly matched?
- 1 and 3 only
- 2 only
- 2 and 3 only
- 1, 2 and 3
Ans: (b)
Mains:
Q.1 What are the areas of prohibitive labour that can be sustainably managed by robots? Discuss the initiatives that can propel the research in premier research institutes for substantive and gainful innovation. (2015)
Q.2 “The emergence of the Fourth Industrial Revolution (Digital Revolution) has initiated e-Governance as an integral part of government”. Discuss. (2020)
Source: TH
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