Dear friend Mohan Lal

Absolutely, my enthusiastic friend Mohan Lal! Let's dive into the realm of artificial intelligence in public health with my passion and vigor.

Firstly, introducing AI into public health is a game-changer, a revolutionary force that can transform the landscape of healthcare. Here's a battle plan to start this AI revolution:

1. **Knowledge Sharing:**

- Rally your troops—health professionals, researchers, policymakers, and tech enthusiasts.

- Initiate knowledge-sharing sessions, webinars, and conferences. Let the collective wisdom flourish.

2. **Case Studies and Success Stories:**

- Share success stories from other fields where AI has made significant impacts.

- Highlight cases where AI has improved diagnostics, treatment plans, and patient outcomes.

3. **Collaboration Platforms:**

- Forge alliances on platforms designed for collaboration.

- Establish online forums or groups where public health professionals can discuss AI applications, challenges, and share insights.

4. **Training Programs:**

- Conduct training programs to bridge the knowledge gap.

- Develop courses on AI applications in public health, catering to various skill levels.

5. **Start Small, Aim Big:**

- Implement pilot projects in specific health areas.

- Showcase the feasibility and benefits of AI applications in controlled environments.

6. **Policy Advocacy:**

- Advocate for policies that support the integration of AI in public health.

- Work with policymakers to create frameworks ensuring ethical use, patient privacy, and data security.

7. **Open Data Initiatives:**

- Encourage the sharing of health data (while respecting privacy).

- Foster an environment where researchers and developers have access to diverse datasets for creating robust AI models.

8. **Community Engagement:**

- Engage with the wider community through social media, newsletters, and public forums.

- Encourage public participation in discussions about the role of AI in shaping their health services.

9. **Show Me the Money:**

- Attract funding for AI projects in public health.

- Collaborate with government bodies, private organizations, and philanthropic foundations.

10. **Continuous Evaluation:**

- Regularly evaluate the impact of AI applications.

- Gather feedback from professionals, patients, and other stakeholders to refine and improve your strategies.

Some of my efforts in this direction are:

Patent System to implement cyber security and institutional strateg...

Patent A portable dongle for cyber security and protection

Patent AUTOMATIC FACE MASK DETECTION DEVICE IN HOSPITALS THROUGH IN...

There are more publications underway so please keep in touch.

Remember, the road to AI-driven public health is an exciting journey, filled with challenges and victories. I say let the AI revolution commence, and may your endeavors bring about a healthier, smarter, and more connected world!

I would like to see AI being used to predict and prevent diseases and epidemics. Hence we can then have a proactive approach rather than a reactive. AI can also be used to discover new and more effective treatments for those that are already ill/have medical conditions.

Some elements about a sector of public health: health and safety at work:

Article Artificial intelligence in the service of health and safety ...

Book Artificial intelligence in the service of occupational safet...

The use of Artificial Intelligence (AI) in public health can be beneficial in enhancing the efficiency, accuracy, and accessibility of healthcare services. A promising area to initiate AI applications is in the collection of relevant and high-quality data. However, caution must be exercised as this also introduces risks and challenges. Handling vast amounts of health data can pose significant privacy risks, with potential consequences such as leakage or unauthorized access to sensitive medical information being severe.

The introduction of artificial intelligence is an irreversible process. Like the Internet, it has both perverse and beneficial effects. We already need to know how to benefit from it, especially in terms of care models, treatment and response to epidemics, in all areas of healthcare.

Starting artificial intelligence (AI) in public health requires a systematic approach. Here are some steps to consider:

1. Identify the problem: Determine specific challenges in public health that can benefit from AI, such as disease surveillance, diagnosis, treatment optimization, or resource allocation.

2. Gather data: Collect relevant data from various sources, including electronic health records, medical literature, wearable devices, and social media. Ensure data privacy and security measures are in place.

3. Clean and preprocess data: Data preprocessing involves cleaning, organizing, and transforming data into a suitable format for AI algorithms. This step is crucial for accurate analysis and insights.

4. Apply AI algorithms: Utilize machine learning, deep learning, and other AI techniques to analyze the data. Develop models that can predict disease outbreaks, identify patterns, classify images, or recommend personalized treatments.

5. Validate and refine models: Validate the AI models using different datasets and evaluate their performance against established benchmarks. Continuously refine and improve the models based on feedback and new data.

6. Integrate AI into workflows: Collaborate with healthcare professionals to integrate AI tools and algorithms into existing workflows. This may involve developing user-friendly interfaces or integration with electronic health record systems.

7. Monitor and evaluate: Continuously monitor the performance and impact of AI applications in public health. Assess their effectiveness, safety, and cost-effectiveness to ensure they provide tangible benefits.

8. Address ethical considerations: Consider ethical implications, such as privacy, bias, and transparency. Develop guidelines and policies to ensure responsible use of AI in public health.

9. Foster collaboration and knowledge sharing: Encourage collaboration between researchers, healthcare providers, policymakers, and technology experts. Share knowledge, experiences, and best practices to advance AI in public health.

10. Adapt and evolve: AI in public health is an evolving field. Stay updated with the latest advancements, research, and regulations to leverage new opportunities and address emerging challenges.

Collaboration among healthcare professionals, data scientists, policymakers, and technology experts is crucial for successful integration of AI in public health initiatives. By following these steps, stakeholders can effectively introduce and leverage AI in public health to improve healthcare outcomes, enhance decision-making, and address public health challenges more efficiently.

Intiate artificial intelligence in public health by uptake of synergist participation of community appropriate technology at household level.

искусственный интеллект полезен при проведении скрининговых исследований, например, на наличие диабетической ретинопатии, глаукомы, возрастной макулодистрофии. Также он может быть полезен при проведении обширных исследований для первичной статической обработки и сбора первичного материала, возможно отбора и первичного анализа материала. В подготовке отчетов также полезен искусственный интеллект