What's Next For AI In Healthcare In 2023? - The Medical Futurist
TLDRIn 2023, AI in healthcare is set to revolutionize the field with adaptive algorithms, regulatory challenges, and integration into various medical specialties. The FDA is developing a comprehensive AI database, while the American College of Radiology provides guidelines for AI use. Large language models will face new regulations, and AI is expected to make significant strides in drug discovery, with increased efficiency and adoption across healthcare.
Takeaways
- π§ AI is a buzzword in healthcare, with rapid developments and applications transforming the field.
- π₯ The FDA is a forward-looking regulatory body that has approved numerous AI applications in healthcare, setting milestones for clinical use.
- π The FDA is developing a comprehensive database for AI-based healthcare technologies, providing crucial information on their intended use, effectiveness, and safety.
- π Adaptive algorithms are self-learning and constantly evolving, presenting new challenges for regulation as they change behavior based on learning processes.
- ποΈ Google's diabetic retinopathy detection algorithm is an example of how adaptive AI can improve accuracy by learning to adjust to varying conditions.
- π The American College of Radiology has introduced guidelines for submitting AI-related studies and for radiologists to approach AI studies, which will be implemented across medical specialties.
- ποΈ Regulatory bodies worldwide are developing frameworks for large language models (LLMs), focusing on safety, transparency, and accountability.
- π« Misuse of LLMs could lead to misinformation or privacy violations, indicating the need for distinct regulation from other AI medical technologies.
- π Drug discovery is a key area where AI is expected to break into the pharmaceutical industry, offering significant time and cost savings.
- π The number of applied AI solutions is expected to increase in established areas such as radiology, oncology, and cardiology, as well as in new areas like mental health.
- π οΈ AI-based tools will be increasingly adopted in healthcare, with professionals experimenting with tools like voice-to-text applications for medical records, enhancing efficiency.
Q & A
What is the buzzword of the year according to the video?
-The buzzword of the year is AI, as it continues to disrupt and transform healthcare.
What is the FDA doing to keep up with the latest AI developments in healthcare?
-The FDA is approving a myriad of applications, marking crucial milestones, and working towards the development of a comprehensive database for AI-based healthcare technologies.
What is the role of the database developed by the FDA for AI applications?
-The database serves as a repository of approved AI applications, providing crucial information about their intended use, effectiveness, and safety.
What is the main challenge for the FDA in regulating AI this year?
-The main challenge is regulating adaptive algorithms, which are self-learning programs that constantly change, learn, and evolve, making it difficult to give a green light to a product that changes significantly over time.
How does an adaptive AI differ from traditional algorithms?
-Adaptive AI algorithms change their behavior using a defined learning process, meaning they are self-learning and constantly evolving, unlike traditional algorithms that work from the data they were fed with.
What is an example of how adaptive AI could revolutionize healthcare?
-An example is Google's diabetic retinopathy detection algorithm, which could learn to adjust to varying image quality and deliver more accurate results as it trains itself to be better.
What has the American College of Radiology done to help professionals understand and utilize AI technologies?
-The American College of Radiology has introduced instructions on how to submit studies, papers, or scientific publications related to AI technology and provided guidance on how radiologists should approach reading an AI study.
Why are large language models (LLMs) facing regulations?
-LLMs are facing regulations to ensure safety, transparency, and accountability, as misuse of elements could lead to the spread of misinformation or even violate patient privacy rights.
What is the impact of AI on drug discovery in the pharmaceutical industry?
-AI is expected to break into the pharmaceutical industry through its effectiveness in drug discovery, predicting which molecules could become potential drugs and designing novel drug candidates in weeks instead of years.
How will AI solutions increase in established areas like radiology, oncology, and cardiology?
-The number of applied AI solutions will increase in these areas due to their established use and the potential for AI to further enhance diagnostic and treatment processes.
What new innovative models for AI in healthcare are expected to emerge?
-New innovative models like paid subscribers accessing an AI chatbot rooted to a human therapist for escalated queries are expected to be developed for various purposes in healthcare.
Outlines
π AI in Healthcare: Current Trends and Future Predictions
Dr. Bartolo Meshku introduces the topic of AI's impact on healthcare, highlighting the FDA's role in approving AI applications and the challenges of regulating adaptive algorithms. The FDA's efforts to create a comprehensive database for AI-based healthcare technologies are discussed, emphasizing the need for robust regulatory mechanisms. Adaptive algorithms, which learn and evolve, are identified as a game-changer in healthcare, but their regulation poses a significant challenge. The American College of Radiology's guidance on AI in radiology is mentioned, along with the potential for AI to revolutionize drug discovery and the integration of AI services in healthcare businesses. The video anticipates increased adoption of AI in various medical fields, including mental health.
π The Expanding Role of AI in Enhancing Healthcare Efficiency
This paragraph delves into the innovative models of AI integration in healthcare, such as AI chatbots with human therapist backup for escalated queries. It discusses the potential for AI to increase efficiency through tools like voice-to-text applications in medical records. The paragraph also touches on the wide range of AI demand tools available beyond medicinal healthcare, which can assist in various tasks from web development to email generation. The summary concludes with an optimistic view of 2023 as a year of challenge and excitement in the tech revolution of healthcare, inviting viewers to subscribe for updates and explore courses on digital health and AI in medicine.
Mindmap
Keywords
π‘AI in Healthcare
π‘FDA
π‘Adaptive Algorithms
π‘Regulatory Mechanisms
π‘American College of Radiology
π‘Large Language Models (LLMs)
π‘Drug Discovery
π‘AI Solutions
π‘Voice to Text Applications
π‘AI Demand Tools
π‘Digital Health Course
Highlights
AI's applications and developments in healthcare are rapidly expanding, making it challenging to keep up with the latest news.
The FDA has approved numerous AI applications in healthcare, marking milestones and paving the way for clinical use.
A comprehensive database for AI-based healthcare technologies is being developed by the FDA to provide crucial information on approved AI applications.
Adaptive algorithms, which self-learn and evolve, will change the regulatory landscape for AI in healthcare.
The American College of Radiology has introduced guidelines for submitting AI-related scientific publications and for radiologists to approach AI studies.
Regulatory bodies worldwide are developing frameworks to govern the use of large language models (LLMs) in healthcare, focusing on safety, transparency, and accountability.
Regulation of LLMs will likely be a new category, distinct from other AI-based medical technologies.
Challenges and confusion in AI regulation may lead to temporary bans in some countries, but the advantages of AI in healthcare are significant.
Companies and healthcare institutions are integrating chatbot-like services into their businesses, with Microsoft and Amazon being major players.
Drug discovery is a key area where AI is expected to break into the pharmaceutical industry, offering significant time and cost savings.
The number of applied AI solutions is expected to increase in established areas such as radiology, oncology, and cardiology, as well as in new areas like mental health.
Innovative models like AI chatbots with human therapists for escalated queries are being developed for mental health.
AI-based tools like voice-to-text applications will increase efficiency and adoption of AI in healthcare by reducing the workload of medical professionals.
A wide selection of AI demand tools, not strictly related to medicinal healthcare, can assist in various tasks from website building to email generation.
2023 is anticipated to be a year of challenges, excitement, and a tech revolution in healthcare, unveiling new solutions in medical knowledge.
The Medical Futurist offers courses on digital health and an introduction to artificial intelligence in medicine and healthcare.