Dr. Ron Razmi discusses his book, AI Doctor: The Rise of Artificial Intelligence in Healthcare, which focuses on the applications of AI in various areas of healthcare. Ron talks about AI as a foundational technology that uses statistical methods to analyze data and understand its meaning. It can be applied to various areas, such as coding and documentation, and can create algorithms to analyze heartbeats and detect abnormal rhythms.   AI Use in Diagnostics In diagnostics, AI can be helpful in analyzing clean structured data, such as radiology files from CAT scans or MRIs. AI can be trained to identify bleeding or abnormalities on these scans, but it must be trained on specific abnormalities. Currently, AI excels in radiology due to the digitized and structured data, but it's not as effective in narrative formats. Ron states that AI's applications in healthcare are vast and deep, and while it's still in its early stages, it has the potential to revolutionize various sectors, including healthcare. AI Tools in Radiology and Triage AI is increasingly being used in various fields, including radiology, dermatology, and sound AI. In radiology, AI tools are helping radiologists identify potential issues that might have been missed in traditional workflows. There are applications that read CAT scans for bleeding and stroke in acute settings, allowing radiologists to quickly identify and treat stroke patients. This helps in regaining function and ensuring patient recovery. AI can also aid in triage, prioritizing tasks based on urgency.    AI in Dermatology In dermatology, AI applications can help diagnose skin lesions. Additionally, sonar technology can be used to monitor people's activity and detect falls. This passive data collection method allows AI to analyze the signals and take action, reducing the need for manual data entry and manual data input. This technology is particularly effective for elderly individuals who may not want to be monitored with cameras, as 50% of falls occur in the bathroom. This technology is particularly useful for those who prefer to stay home but still need constant monitoring, such as those in assisted or independent living facilities.    AI in Cardiology In cardiology, AI tools can help read EKGs, which are crucial for diagnosing heart conditions. Historically, algorithms have been used to read EKGs, but they were often basic and inaccurate. AI has shown great promise in finding abnormalities on single lead data collection, as it can discern the rhythm of an EKG from a live core or smartphone application. This field-based data collection could significantly reduce the simple analytic and downstream work needed by clinicians in the medical staff.    AI in Therapeutics AI takes action in therapeutics, such as providing assistance to patients with mental health issues. AI chatbots can interact with patients who need help and provide frontline assistance until they see a mental health professional. Generative AI has improved natural language processing capabilities, which has been a problem area for AI in healthcare due to the heavy use of medical jargon in doctor's notes. This will allow for more efficient interactions with healthcare consumers and better guidance in their care. However, there is still much work to be done in this promising area.   Technology and Medication Adherence in Healthcare The conversation turns to medication adherence, which is a significant problem in healthcare. Long-term studies show that people who have had a heart attack are more likely to stay compliant with their medications, with the refill rate for statins being the highest documented rate. However, most people do not follow their prescription advice. Technology is part of the solution to this problem. AI technology can potentially analyze data and interact with patients at the appropriate moment to ensure they are aware of the needs, issues, and dates of medication use or the lack of, whi