Challenges to AI in Indian Healthcare Data Analytics

AI is poised to revolutionize India's healthcare sector, with estimates suggesting a $967 billion boost to the economy by 2035

However, significant hurdles need to be addressed.

Key Challenges:

Data Biases: AI models trained on biased data can lead to inaccurate diagnoses and discrimination. India's diverse population makes this a major concern.

Lack of Transparency: "Black box" AI algorithms raise questions about patient safety and accountability. Doctors need to understand how AI tools arrive at decisions.

Regulation Gap: Existing laws don't adequately address AI-related issues like liability for errors or data privacy.

The Road Ahead:

Rigorous Testing: AI tools must undergo thorough testing to minimize bias and ensure accurate outcomes.

Regulatory Framework: India needs robust legal frameworks to govern AI use in healthcare, addressing liability, data protection, and cybersecurity.

Transparency and Education: Healthcare professionals need training on AI capabilities and limitations to foster trust and effective integration.

While challenges exist, AI's potential to improve diagnosis, treatment, and drug discovery in India is undeniable. By addressing these concerns, India can unlock the power of AI for a healthier future.