🔍 AI Exploration: 🤖 Bridging Biases, 💡 Primer on AI in Medicine, 🏥 Medical Education with ChatGPT, and More!
Educational Supplement to The 'Med AI' Capsule Newsletter 🤖🩺🚀
Dear Med AI Enthusiast,
Welcome to this exclusive weekly feature, a carefully curated blend of valuable educational insights, complimenting your journey through The ‘Med AI’ Capsule - your essential weekly news digest 📰 on the dynamic intersection of artificial intelligence and other emerging technologies shaping the future of medicine. ⚕️
In today’s supplement:
1 Concept Made Easy
1 Knowledge Resource
1 Research Deep Dive
Industry Showcase - 3 Innovative Startups/ Companies
GenAI Corner
Test Your Knowledge
Reading Time: 5-7 minutes
Concept Made Easy 👨🏫
BIAS 📊
Bias in AI is like having a detective with a favorite suspect. 🕵️♂️
Picture a detective (AI) who always thinks the butler did it, no matter what. 🧑🍳
Similarly, AI can make mistakes because it favors certain groups or relies on incomplete information. ℹ️
For instance, let's say we have an AI that assists in diagnosing diseases. 🩻
If it is primarily trained on data of adult patients and lacks information on children, it might not be as accurate when diagnosing kids. 👶
This bias can lead to incorrect diagnoses or delayed treatments. 💉
Another example is if the AI is trained using data representing only a specific racial or ethnic group. 🌝🌚
In such cases, it may not work as effectively for individuals from different backgrounds, resulting in unequal healthcare outcomes. ⚖️
Now, why does bias appear in the first place in AI, especially medical AI? 🤖
The culprit lies in the data itself. 📊
Sometimes, the information used to train AI can be incomplete or unrepresentative. ℹ️
If the data is predominantly from one group, the AI may lack crucial knowledge about other groups. 🧑🦯
Additionally, the algorithms used to analyze the data can accidentally reinforce existing biases in society. 👥
Bias in medical AI is a big deal because it directly impacts people's health and can lead to unfair treatment. 🏥
Just imagine if our detective's bias prevents them from identifying a serious illness, endangering lives and creating disparities in healthcare provision. ⚕️
To address this issue, we need to ensure that AI is trained on diverse and representative data. 🗂️
By doing so, we can create more accurate and fair AI tools that benefit everyone, regardless of their age, gender, race, or other factors. ⚖️
As a health professional, understanding bias in medical AI is crucial. 🎯
By advocating for unbiased AI tools, raising awareness, and contributing to the development of equitable healthcare practices, you can help pave the way for a future where AI enhances patient care for all individuals. 🌟👩⚕️👨⚕️
Knowledge Resource 📚
This is a comprehensive lecture by Dr. Anthony Chang on the topic of artificial intelligence in medicine. It's the first of a two-part primer designed as an introduction to AI in the medical field. Here's a brief summary of the key points covered:
Why AI in Medicine Now?: Dr. Chang discusses the need for AI in medicine due to information overload, with medical knowledge doubling every few months. He emphasizes AI's potential in updating old methodologies, balancing clinical decision-making, and reducing biases in medical practices.
History of AI: The lecture traces the origins of AI, highlighting key figures like Alan Turing and milestones such as IBM's Deep Blue and Watson, and DeepMind's achievements in games like Chess, Jeopardy, and Go.
Evolution of AI: Dr. Chang explains the evolution from traditional automation to expert systems in the '70s and '80s, and the rise of machine learning and deep learning in recent decades. He stresses the significance of cloud computing, GPUs, and the explosion of healthcare data in advancing AI.
Data and AI in Healthcare: The lecture touches on the challenges and complexity of healthcare data and the importance of understanding the continuum from data to wisdom in AI applications.
AI Techniques and Applications: Dr. Chang delves into various AI methodologies, including supervised and unsupervised learning, regression analysis, decision trees, and clustering. He also explains the concept of ensemble learning.
AI in Medicine Today: The current state of AI in medicine is described as 'narrow' or 'weak', specialized in specific tasks. The expectation is to eventually develop 'general' or 'strong' AI capable of multiple, complex tasks.
Types of AI: He categorizes AI into assisted, augmented, and autonomous types, each with different levels of human involvement and application in various fields.
Future of AI in Medicine: The talk concludes with a look toward the future, where AI could significantly impact areas like precision medicine and healthcare delivery.
Dr. Chang's lecture is insightful for anyone interested in the intersection of AI and healthcare, offering a thorough introduction to the subject.
Research Deep Dive 🔬
Oh DJ, Hwang Y, Kim SH, Nam JH, Jung MK, Lim YJ. Reading of small bowel capsule endoscopy after frame reduction using an artificial intelligence algorithm. BMC Gastroenterol. 2024 Feb 22;24(1):80. doi: 10.1186/s12876-024-03156-4. PMID: 38388860; PMCID: PMC10885475.
The study evaluates the impact of removing poorly visualized images using an artificial intelligence algorithm on the diagnosis and reading time of small bowel capsule endoscopy (SBCE).
Key insights and lessons learned:
Utilizing a validated AI algorithm to remove poorly visualized images significantly reduces reading time during SBCE interpretation without compromising diagnostic concordance.
The study highlights the potential of AI assistance in improving efficiency and accuracy in SBCE diagnosis, particularly in cases with large numbers of images.
Removing poorly visualized images does not result in the omission of lesions, ensuring the reliability of the diagnostic process.
Both experienced endoscopists and AI can work synergistically to enhance diagnostic outcomes in SBCE, suggesting a promising role for AI integration in clinical practice.
Limitations:
AI may accidentally delete important images showing significant lesions, especially when they're obscured by blood or debris, potentially leading to missed diagnoses.
Few participating endoscopists and SBCE cases were included because the study was conducted at a single center, limiting the generalizability of the results.
The SBCE device used might not be available in all regions, necessitating further research on other devices.
Developing software capable of real-time removal of poorly visualized images and merging remaining images during SBCE reading is necessary, as the current process requires manual intervention.
The study suggests that AI frame reduction methods can be used for SBCE reading, aiding in faster interpretation, although further research is needed to fully trust AI-assisted lesion detection alone, positioning frame reduction reading as a potential bridge between conventional and AI-assisted reading in clinical practice.
Industry Showcase 👨🏭
Tricog - offer virtual cardiology services to improve patient outcomes and reduce the time to treatment. Their product portfolio includes InstaECG, a cloud-connected device that analyzes and interprets ECG reports within 10 minutes, and InstaEcho, an AI-powered device that assists doctors in obtaining accurate and fast echocardiograms for diagnosing conditions like heart failure.
HealthifyMe - a Bengaluru-based health and wellness application. Leveraging AI, the app monitors calorie intake and provides dietary recommendations, tips, and nutritious recipes. It also features an AI assistant named Ria, which answers users' fitness and health queries in 10 languages.
Qure.AI - a Mumbai-based healthcare-tech startup using AI to interpret radiology scans within seconds. Their deep-learning algorithms are designed to understand radiology images, aiming to make healthcare solutions more affordable and accessible. This helps professionals detect diseases efficiently and accurately.
GenAI Corner 🤖
Tutorial: Leveraging ChatGPT for Medical Education and Student Engagement
Step 1: Identify the Educational Objective
First, clarify what you aim to achieve with your educational content. Are you creating a module on a specific disease, teaching clinical skills, discussing case studies, or exploring medical ethics? Knowing your objective will guide the development of your content.
Step 2: Collect and Verify Information
Gather the necessary information to support your educational goals. This may include clinical guidelines, research articles, textbooks, or expert opinions. Ensure that all information is up-to-date, accurate, and from reputable sources to maintain educational integrity.
Step 3: Choose the Format and Tone
Decide how you will present the material. Will it be through lectures, interactive case studies, quizzes, or discussion prompts? Consider your audience, typically medical students or residents, and adopt a tone that is informative, engaging, and conducive to learning.
Step 4: Draft a Detailed Prompt for ChatGPT
Compose a specific prompt for ChatGPT that outlines what you need. Include the educational goals, key information points, intended audience, and any preferences for presentation style. For example:
"Develop an interactive case study on managing Type 2 Diabetes Mellitus for medical students. The study should include patient history, test results, treatment options, and follow-up care. Incorporate questions to provoke critical thinking and discussion. Aim for an engaging and educational format."Step 5: Generate the Educational Content
Use ChatGPT to create a draft of your educational material based on the prompt. Ensure the content is aligned with your objectives, accurately conveys medical knowledge, and is presented in an engaging manner for students.
Step 6: Personalize and Refine the Material
Review the generated content, adding your own expertise, clinical experiences, or additional educational resources to enhance its value. Adjust the tone and complexity to suit the learning level of your audience, ensuring the material is both challenging and accessible.
Step 7: Implement Interactive Elements (Optional)
If applicable, integrate interactive components such as quizzes, simulations, or discussion boards to foster active learning. These elements can help students apply knowledge, practice clinical reasoning, and engage more deeply with the material.
Step 8: Review for Educational Compliance
Before deploying your content, ensure it meets educational standards and guidelines, respects patient confidentiality (if real cases are used), and is accessible to all students. This final check ensures that your material is ethically sound and educationally effective.
Test Your Knowledge 🧩
Your feedback is crucial to me, as it helps me understand your interests and improve my offerings. I would appreciate it if you could take a few minutes to share your thoughts about what you've enjoyed and what you think I could do better - https://forms.gle/fUJZhjUBJe9ojySg6
Stay tuned for our upcoming editions as we explore the latest breakthroughs and dive deep into the transformative power of artificial intelligence and emerging technologies, shaping a healthier future. 🚀
Warm regards,
Thank you for acknowledging. Ultimately the benefit should be passed on to the end user whose access and affordability to quality health care is always been paradoxical and who is at the receiving end and is a subject for exploitation with the existing over commercialized global health care system. Hopefully new innovative technology "AI in health" focuses on it and shouldn't become another commercial tool to be used to exploit the end user.
AI in medicine is unique unlike use of AI in other areas due to the fact that it has an inherant biological variations . Success of AI in medicine depends on how best those variabilities are addressed