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Home Innovations & Investing

AI and Medicine Don’t Mix

Medicine was never meant to be standardized

Jay K Joshi by Jay K Joshi
May 8, 2024
in Innovations & Investing
0
AI and Medicine Don't Mix

Planet Volumes

Artificial intelligence (AI) has revolutionized many industries,  including the healthcare system but when it comes to medicine, there is a fear that it may not work well due to patients’ aversion to standardized care and control from AI systems. However, the integration of AI in healthcare has the potential to greatly benefit patients and improve overall healthcare outcomes.

One of the primary concerns about AI in medicine is the fear of standardized care. Patients often prefer personalized treatment plans tailored to their specific needs and preferences. They fear that AI algorithms may lead to a one-size-fits-all approach that ignores the individuality of each patient. However, AI can actually enhance personalized medicine by analyzing vast amounts of data to identify patterns and trends that can inform more targeted and effective treatments. AI can help healthcare providers deliver more personalized and precise care that is tailored to each patient’s unique needs, showcasing innovations in healthcare.

Another concern is the perceived loss of control from AI systems in medicine. Patients may feel uncomfortable with the idea of AI making decisions about their healthcare without human oversight. However, AI can be used as a tool to assist healthcare providers in making more informed decisions, rather than replacing human judgment altogether. AI can analyze complex medical data, detect patterns, and offer recommendations to healthcare providers, but ultimately, the final decision lies with the human caregiver.

Incorporating AI in medicine can lead to more efficient and accurate diagnoses, improve treatment planning, and enhance patient outcomes. AI can help healthcare providers in diagnosing diseases at an early stage, predicting patient outcomes, and monitoring patients’ progress in real-time. By streamlining administrative tasks and reducing errors, AI can also help healthcare organizations save time and resources, allowing them to focus more on providing quality care to patients.

While there may be concerns about AI in medicine, the general consensus currently is that the benefits of integrating AI systems far outweigh the drawbacks. Patients can still receive personalized care and maintain control over their healthcare decisions, while leveraging the power of AI to improve overall healthcare delivery. It is essential for healthcare providers to work collaboratively with AI systems to ensure that patients receive the best possible care while maintaining a human touch in the healthcare experience, an important aspect of healthcare policy.

Yes, it is true that AI has the potential to revolutionize the field of medicine by improving diagnostic accuracy, treatment outcomes, and overall efficiency. However, along with its benefits, there are also significant risks associated with the use of AI in medicine. Rather than dismiss those risks, we should pay close attention to them and listen to patients when they express concerns around those risks.

One major risk of AI in medicine is the potential for errors or biases in the algorithms used to make medical decisions. AI systems rely on data to learn and make predictions, and if the data is biased or incomplete, it can lead to inaccurate diagnoses or treatment recommendations. Additionally, AI systems may not always be able to explain the reasoning behind their decisions, which can be concerning when it comes to matters of life and death.

Another risk of AI in medicine is the threat to patient privacy and data security. Medical data is highly sensitive and confidential, and the use of AI systems to analyze this data raises concerns about who has access to it and how it is being used. Unauthorized access or misuse of this data could have serious consequences for patients and healthcare providers.

There is a fear among patients about the loss of the human touch in healthcare. Many patients value the personal connection they have with their healthcare providers and may be hesitant to trust AI systems with their care. Patients may also be concerned about the lack of empathy and understanding that AI systems can provide compared to a human healthcare provider.

Overall, these risks contribute to the reluctance of patients to adopt AI in medicine. Despite the potential benefits of AI, patients may be hesitant to fully embrace this technology until these risks are addressed and mitigated. Healthcare providers and policymakers must carefully consider these risks and work towards building trust and transparency in the use of AI in medicine to ensure its successful adoption.

Ultimately, the adoption of AI will not take place broadly nor at a systemic level. Rather, it will be adopted on a case by case basis specific to the patients’ needs. AI will not standardized medicine nor make it more efficient as a whole. It will make specific processes and procedures more effective than before.

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Jay K Joshi

Jay K Joshi

Dr. Joshi is the founding editor of Daily Remedy.

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Videos

In this episode, the host discusses the significance of large language models (LLMs) in healthcare, their applications, and the challenges they face. The conversation highlights the importance of simplicity in model design and the necessity of integrating patient feedback to enhance the effectiveness of LLMs in clinical settings.

Takeaways
LLMs are becoming integral in healthcare.
They can help determine costs and service options.
Hallucination in LLMs can lead to misinformation.
LLMs can produce inconsistent answers based on input.
Simplicity in LLMs is often more effective than complexity.
Patient behavior should guide LLM development.
Integrating patient feedback is crucial for accuracy.
Pre-training models with patient input enhances relevance.
Healthcare providers must understand LLM limitations.
The best LLMs will focus on patient-centered care.

Chapters

00:00 Introduction to LLMs in Healthcare
05:16 The Importance of Simplicity in LLMs
The Future of LLMs in HealthcareDaily Remedy
YouTube Video U1u-IYdpeEk
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AI Regulation and Deployment Is Now a Core Healthcare Issue

Clinical Reads

Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

by Daily Remedy
February 1, 2026
0

Health systems are increasingly deploying ambient artificial intelligence tools that listen to clinical encounters and automatically generate draft visit notes. These systems are intended to reduce documentation burden and allow clinicians to focus more directly on patient interaction. At the same time, they raise unresolved questions about patient consent, data handling, factual accuracy, and legal responsibility for machine‑generated records. Recent policy discussions and legal actions suggest that adoption is moving faster than formal oversight frameworks. The practical clinical question is...

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