How can you encourage AI and healthcare experts to collaborate?

I researched and collaborated with healthcare, epidemiology, and vaccination companies in Vietnam to understand their real-world needs and challenges. I learned about patient perspectives and the difficulties healthcare professionals face. With the goal of streamlining treatment processes, reducing the patient-provider gap, and improving vaccination accuracy, I gained insights into specific issues. I represented medical professionals to provide insights into AI capabilities and limitations. Finally, we proposed efficient solutions and implemented AI technology step by step in the healthcare sector.

Some ways to get started: 1. Understand the need 2. Make sure the AI you use is solving the need 3. Show experts how it works and prove that it is not an rocket science 4. Explain how it works and how it will look like in future, make sure they feel safe using it

This is the issue I mentioned earlier. All experts understand it, and they are trying to ask AI experts like me about common ground and safe solutions. Safety is the most crucial aspect. However, the most critical factor in the communication and execution process is the interaction between humans and machines. Therefore, AI can serve as a source of knowledge for advisory purposes before providing operational guidance. AI can guide processes and monitor them. Ultimately, AI can monitor and measure accuracy on each device, recognize pain sensations, reactions, vision, pupils, and various other medical indicators, measured by signal-collecting devices from patients to provide necessary reminders.

Healthcare experts should be motivated to share data by empressing to them the capabilities of what is behind the data sharing process of great AI model the automate and assist in the diagnosis and treatment. But this must be happened by keeping into consideration the to make the healthcare experts feel safe when sharing data by providing real governance policies and showing how data is processed and insights are extracted anonymously by keeping all private and personal data unexposed.

To encourage collaboration between AI and healthcare experts, rigorous testing and iteration are essential. Rather than settling for the first solution, they should evaluate it against the problem, real-world scenarios, and user feedback. This iterative process helps refine the solution and uncover new challenges, fostering a productive collaboration.