FDA UPDATES – October 2023
October 20, 20232017
November 26, 2023An AI revolution is brewing in medicine. What will it look like?
In the heart of the ever-evolving healthcare landscape, a groundbreaking revolution is quietly taking shape, promising to transform how we approach medicine...
In the heart of the ever-evolving healthcare landscape, a groundbreaking revolution is quietly taking shape, promising to transform how we approach medicine. The fusion of artificial intelligence and healthcare has paved the way for innovative solutions, sparking what can only be described as an AI revolution in medicine. But what will this revolution look like? How will it impact patient care, diagnostics, and the overall healthcare experience?
How Artificial Intelligence is Changing Health Care
The integration of artificial intelligence (AI) into the field of medicine is rapidly reshaping the way healthcare is approached and delivered. At the University of Colorado Anschutz Medical Campus, AI’s potential in healthcare is a constant topic of exploration. From enhancing diagnostics to revolutionizing patient care, faculty members and students are actively engaging with AI technologies. For instance, AI-assisted diagnostic tools, like automated retinal image analysis, are already being used in ophthalmology to detect diseases early. Researchers like Malik Kahook, MD, are pioneering the use of AI in creating innovative solutions like the SpyGlass device for delivering glaucoma medication.
Machine learning techniques, from simple implementations to complex personalized medicine treatments, are being harnessed to process vast datasets, improving the accuracy of diagnoses and treatment plans. However, challenges exist, such as addressing biases in AI tools and determining the balance between technology and human expertise. Medical educators like Shanta Zimmer, MD, are actively integrating AI into the curriculum, fostering critical thinking skills among students. While skepticism exists, the consensus is clear: AI is not just a tool but an integral part of the future of medicine, where collaboration and understanding its limits are key to unlocking its full potential.(1)
Pursuing the Ethics of Artificial Intelligence in Healthcare
Cedars-Sinai is at the forefront of the ethical integration of artificial intelligence (AI) in healthcare, recognizing the transformative potential of AI while emphasizing the importance of responsible implementation. Mike Thompson, Vice President of Enterprise Data Intelligence at Cedars-Sinai, stresses the significance of ethical considerations in AI applications, particularly in healthcare, where the stakes are high. Ethical guidelines are crucial to ensuring fairness, safety, and equity, especially as AI continues to advance. Cedars-Sinai has developed a comprehensive framework for the ethical development and use of AI, focusing on the impact on patients, physicians, and the healthcare community. This approach involves ongoing monitoring and review, emphasizing the need for adaptive AI systems that are continually assessed for fairness and reliability. By prioritizing ethics and equity, Cedars-Sinai aims to harness the power of AI for the benefit of all, emphasizing the importance of trustworthiness and accountability in the evolving landscape of healthcare technology.(2)
Cedars-Sinai is at the forefront of the ethical integration of artificial intelligence (AI) in healthcare, recognizing the transformative potential of AI while emphasizing the importance of responsible implementation. Mike Thompson, Vice President of Enterprise Data Intelligence at Cedars-Sinai, stresses the significance of ethical considerations in AI applications, particularly in healthcare, where the stakes are high. Ethical guidelines are crucial to ensuring fairness, safety, and equity, especially as AI continues to advance.
Cedars-Sinai has developed a comprehensive framework for the ethical development and use of AI, focusing on the impact on patients, physicians, and the healthcare community. This approach involves ongoing monitoring and review, emphasizing the need for adaptive AI systems that are continually assessed for fairness and reliability. By prioritizing ethics and equity, Cedars-Sinai aims to harness the power of AI for the benefit of all, emphasizing the importance of trustworthiness and accountability in the evolving landscape of healthcare technology.(2)
A medical AI revolution is on the horizon, but what will it entail?
AI in medicine is rapidly evolving, with increasing applications in medical imaging. However, the current AI tools are seen as support systems for clinicians rather than replacements. Despite the rapid development of AI technology, many physicians remain cautious and, in some cases, skeptical about its performance and effectiveness. One challenge the current AI tools face is their narrow focus on specific tasks and diseases rather than providing comprehensive interpretations of medical examinations. Additionally, there are concerns about the quality and safety of AI applications, leading to doubts and, in some cases, abandonment of these technologies. A new approach called generalist medical AI, inspired by large language models like ChatGPT, aims to address these limitations .(3)
AI in medicine is rapidly evolving, with increasing applications in medical imaging. However, the current AI tools are seen as support systems for clinicians rather than replacements. Despite the rapid development of AI technology, many physicians remain cautious and, in some cases, skeptical about its performance and effectiveness. One challenge the current AI tools face is their narrow focus on specific tasks and diseases rather than providing comprehensive interpretations of medical examinations.
Additionally, there are concerns about the quality and safety of AI applications, leading to doubts and, in some cases, abandonment of these technologies. A new approach called generalist medical AI, inspired by large language models like ChatGPT, aims to address these limitations .These models, trained on massive datasets, can be adapted for various tasks, potentially acting more like physicians, assessing anomalies comprehensively and assimilating them into diagnoses. While the concept is promising, there are challenges ahead, and researchers are working towards demonstrating the safe and effective use of these generalist medical AI tools in clinical settings.(3)
Some AI chatbots provide racist health information
It has come to light that certain AI chatbots are disseminating racist health information. Recent studies have revealed that several widely used artificial intelligence models, including OpenAI’s ChatGPT and Google’s Bard, have provided responses based on debunked and racially biased medical data. When asked about kidney function and lung capacity, these chatbots used race-based equations that have long been discredited in the medical community. This concerning revelation emphasizes the urgent need for comprehensive oversight and regulation in the integration of AI technologies into healthcare, ensuring that these systems do not perpetuate racial biases or disseminate inaccurate medical information. The consequences of AI chatbots providing racist health information are deeply troubling, as they can exacerbate existing health disparities and lead to misdiagnosis or delayed care for minority communities.(4)
It has come to light that certain AI chatbots are disseminating racist health information. Recent studies have revealed that several widely used artificial intelligence models, including OpenAI’s ChatGPT and Google’s Bard, have provided responses based on debunked and racially biased medical data. When asked about kidney function and lung capacity, these chatbots used race-based equations that have long been discredited in the medical community.
This concerning revelation emphasizes the urgent need for comprehensive oversight and regulation in the integration of AI technologies into healthcare, ensuring that these systems do not perpetuate racial biases or disseminate inaccurate medical information. The consequences of AI chatbots providing racist health information are deeply troubling, as they can exacerbate existing health disparities and lead to misdiagnosis or delayed care for minority communities. Inaccurate information based on race reinforces harmful stereotypes and biases, perpetuating systemic inequalities in healthcare. Addressing this issue requires a collaborative effort between tech developers, healthcare professionals, and policymakers to ensure that AI algorithms are rigorously reviewed, free from racial biases, and grounded in evidence-based medical knowledge. Ethical guidelines and regulations must be established to guarantee that AI technologies are deployed responsibly, promoting equitable healthcare outcomes for all patients, regardless of race or ethnicity.(4)
AI tool effectively detects distress in hospital workers' conversation
A recent study led by researchers at NYU Grossman School of Medicine utilized natural language processing (NLP) to analyze therapy transcripts from healthcare workers during the early days of the COVID-19 pandemic. The study, published in the Journal of Medical Internet Research AI, identified psychological distress markers by examining conversation themes. Healthcare workers who discussed topics such as working in hospital units, lack of sleep, and mood issues were more likely to be diagnosed with anxiety and depression. The study suggests that NLP could become an effective screening tool for detecting and tracking anxiety and depression symptoms. The researchers also plan to explore how discussion topics change over time as therapy progresses, providing valuable insights into mental health patterns in healthcare workers.(5)
A recent study led by researchers at NYU Grossman School of Medicine utilized natural language processing (NLP) to analyze therapy transcripts from healthcare workers during the early days of the COVID-19 pandemic. The study, published in the Journal of Medical Internet Research AI, identified psychological distress markers by examining conversation themes. Healthcare workers who discussed topics such as working in hospital units, lack of sleep, and mood issues were more likely to be diagnosed with anxiety and depression.
The study suggests that NLP could become an effective screening tool for detecting and tracking anxiety and depression symptoms. The researchers also plan to explore how discussion topics change over time as therapy progresses, providing valuable insights into mental health patterns in healthcare workers.(5)
Arterys: Pioneering 4D Flow Technology and Revolutionizing Radiology
Canon Medical has invested £14 million ($17 million) in a new diagnostics and sports facility in Sheffield, UK, which will house some of the company’s top medical devices and serve as the new home for basketball teams the Sheffield Sharks and Hatters. The center is focused on sports medicine and aims to process around 5,000 patients a month, 20% of whom will be professional athletes. The facility will offer quick diagnostics and customized recovery regimens for injured players, with the capacity for minor surgeries. For Canon, the facility provides valuable data for its AI diagnostics tool, which is still in development. The company aims to go beyond diagnosing patients and hopes to predict diseases using biomarkers in the future.(6)
However, Canon is taking a cautious approach and plans to ensure the long-term accuracy of its AI before bringing it to market, comparing its AI with other baseline AI models and doctors in real-time to maintain accuracy. Canon’s focus on safety and accuracy, along with the unique data gathered from elite athletes, positions the company well in the AI-driven medical industry.(6)
Canon Medical has invested £14 million ($17 million) in a new diagnostics and sports facility in Sheffield, UK, which will house some of the company’s top medical devices and serve as the new home for basketball teams the Sheffield Sharks and Hatters. The center is focused on sports medicine and aims to process around 5,000 patients a month, 20% of whom will be professional athletes. The facility will offer quick diagnostics and customized recovery regimens for injured players, with the capacity for minor surgeries.
For Canon, the facility provides valuable data for its AI diagnostics tool, which is still in development. The company aims to go beyond diagnosing patients and hopes to predict diseases using biomarkers in the future.(6)