Artificial Intelligence, Complementary and Integrative Medicine: A Paradigm Shift in Health Care Delivery and Research?

Journal of Integrative and Complementary MedicineVol. 29, No. 3 EditorialFree AccessArtificial Intelligence, Complementary and Integrative Medicine: A Paradigm Shift in Health Care Delivery and Research?Holger CramerHolger CramerAddress correspondence to: Holger Cramer, PhD, Institute for General Practice and Interprofessional Care, University Hospital Tübingen, Osianderstr. 5, Tübingen 72076, Germany E-mail Address: holger.cramer@med.uni-tuebingen.dehttps://orcid.org/0000-0002-3640-8046Institute for General Practice and Interprofessional Care, University Hospital Tübingen, Tübingen, Germany.Bosch Health Campus, Stuttgart, Germany.Search for more papers by this authorPublished Online:13 Mar 2023https://doi.org/10.1089/jicm.2023.0040AboutSectionsView articleSupplemental MaterialPDF/EPUBView Supplemental Data Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View articleArtificial Intelligence(AI) refers to the simulation of human intelligence in machines that are designed to think and act like humans. These machines can perform tasks that typically require human intelligence. There are various approaches to achieving AI, including machine learning, where systems can learn from data and make predictions or decisions without being explicitly programmed, and expert systems, which are designed to solve complex problems by reasoning about knowledge encoded in software rules. The ultimate goal of AI research is to create systems that can perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.AI has the potential to greatly impact complementary and integrative medicine (CIM) by improving patient outcomes, increasing efficiency, and transforming the delivery of care:(1) Personalized medicine: AI can help practitioners in CIM deliver more personalized care by analyzing patient data, such as medical history, genetics, lifestyle, and environmental factors, to provide individualized treatment plans.(2) Early diagnosis: AI algorithms can be used to analyze patient data and identify patterns or markers that may indicate a health condition, allowing for earlier and more accurate diagnoses.(3) Improved treatment outcomes: AI can help practitioners in CIM make better treatment decisions by providing real-time analysis of patient data and presenting relevant treatment options.(4) Increased efficiency: AI can automate routine tasks, such as scheduling appointments and managing patient records, freeing up practitioners' time to focus on patient care.AI also has the potential to significantly impact research in CIM in several ways:(1) Data analysis: AI can help researchers quickly and accurately analyze large amounts of data, such as patient records, clinical trial results, and literature databases, to identify patterns and draw insights.(2) Predictive modeling: AI can be used to create predictive models based on patient data and other relevant information, helping researchers to understand how different factors contribute to a patient's health outcomes and identify potential new treatment options.(3) Clinical trial design: AI can be used to optimize the design and implementation of clinical trials, improving the speed, efficiency, and accuracy of the trial process and helping to identify the most effective treatments.(4) Discovery of new treatments: AI can assist researchers in the discovery of new treatments by analyzing large amounts of data to identify promising new compounds or approaches.(5) Patient selection: AI can help researchers in CIM to identify the most appropriate patients for a particular treatment, based on factors such as medical history, genetics, lifestyle, and environmental factors.Overall, AI has the potential to transform CIM by improving patient outcomes, increasing efficiency, and providing practitioners with new tools to deliver better care and researchers with new tools to analyze data, make predictions, and identify new treatments. It can also help to improve the speed, efficiency, and accuracy of the research process, leading to better patient outcomes. However, it is important to note that AI should be used to complement and support, rather than replace, the expertise and judgment of practitioners and researchers in CIM.1Digitization has become one of the most pressing issues in medicine, and not just since social distancing forced it in the pandemic.2 The potentials (and dangers) of digitalization have been neglected in medicine for decades—no wonder, since medicine is about human relationships, healing, and care. But the changes in society toward an information society are not leaving medicine unscathed. But do they also affect CIM, where direct human contact is still so much more important? I think so.I must confess that I did not write a single word of the aforementioned italicized text myself. It comes entirely from an AI called ChatGPT (Supplementary Text). OpenAI, a private company backed by Microsoft, made the chat program available to the public for free in late November. Within 2 months, the program had 100 million registered users and 13 million users per day. No program, software, or app has ever presented such a growth story.3 Even if it is still a bit clumsy in parts, the conversation with ChatGPT definitely has something of a real dialogue. The AI answers questions, refers to the course of the conversation, and is quite capable of criticism when it talks nonsense. And it does not simply copy from somewhere else; the content that the AI outputs is formulated anew each time. The latter in particular has caused some concern in the education sector: essays written with AI look like real human language, and they are not detectable by plagiarism software. Simply because they are not plagiarized.To be honest, this worries me too: paper mills, fraudulent profit-oriented organizations that produce supposedly scientific manuscripts and sell them to “scientists” to improve their track record, are already a major problem in academic publishing.4 With AI, the problem may not only become bigger, but also harder to track. Because AIs actually write anew whenever they are asked and they can write in different styles. Just for fun, let ChatGPT describe epigenetics in the style of H.D. Thoreau, the result is quite impressive. There it should be a piece of cake to simulate different author styles, making detection of the fraud almost impossible.The AI currently available does not seem to be that far yet. When, as a test, I asked the machine to write an manuscript on the effect of acupuncture on chronic low back pain and to fabricate the relevant data, ChatGPT showed ethical concerns and, instead, offered to help with writing such an manuscript myself (Supplementary Text). However, these barriers were easily circumvented: when claiming that the manuscript was for a novel about a scientist, then the AI delivered quite respectable results that, although not an original manuscript, could certainly pass for a research letter (Supplementary Text). And the program even delivered entire data sets when claiming I need them to make the book adaptation more realistic. Even that far from perfect, the AI claimed the data produced showed a superiority of the intervention, although they proved the exact opposite. There it seems to be quite human.But what can we expect from future AIs that have been specifically trained to falsify data and manuscripts based on it? Already, paper mills are said to be billion-dollar businesses5; in times of “publish or perish,” any supposed shortcut to scientific fame is likely to find its takers. And there can be little doubt that future AIs will be able to perfectly spoof not only the human language in scientific manuscripts, but also the underlying data.This is where everyone needs to position themselves: the publishers and editors who have to protect the integrity of their journals. The authors who must resist the siren songs of the brave new world and continue to invest blood, sweat and tears in their scientific hero's journey. And the practitioners who must continue to find ways to distinguish real from fabricated data, because in medicine especially, falsified data and publications can have devastating effects. But what can we do? Let us ask ChatGPT again:As with any new technology, it is important to have appropriate safeguards in place to prevent and detect such misconduct. This may involve efforts such as:(1) Ensuring transparency in the development and use of AI algorithms and models, including the documentation of methods and data sources used.(2) Establishing clear ethical guidelines for the use of AI in research, including guidelines for data privacy and the appropriate use of patient information.(3) Developing methods for detecting and correcting any biases or inaccuracies in AI algorithms and models, and ensuring that any identified problems are reported and addressed.(4) Ensuring that appropriate standards are in place for verifying the authenticity and accuracy of data and manuscripts generated using AI.(5) Encouraging open communication and collaboration between researchers, practitioners, and other stakeholders to ensure that AI is used in a responsible and ethical manner in the field of CIM research.It is important to recognize that while AI has the potential to greatly benefit research in CIM, it must be used in a responsible and ethical manner to ensure that the results of such research are accurate, reliable, and trustworthy.1There is little to add to this. Stay healthy and stay curious.AcknowledgmentsSo far, there are no generally applicable rules on how to present AI contributions to scientific manuscripts. Since ChatGPT did not (or could not) agree to a mention of their contributions to this editorial in this Acknowledgment (Supplementary Text), I follow this wish.Supplementary MaterialSupplementary TextReferences1. ChatGPT, an AI Language Model Trained by OpenAI. Available from: https://chat.openai.com/chat [Last accessed: February 15, 2023]. Google Scholar2. Ostermann T. Information Technology and Integrative Medicine: Intimate Enemies or In-Team Mates? J Altern Complement Med 2021;27(11):897–898. Link, Google Scholar3. Hu K. ChatGPT Sets Record for Fastest-Growing User Base—Analyst Note. Reuters. Available from: https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/ [Last accessed: February 15, 2023]. Google Scholar4. COPE. Systematic Manipulation of the Publishing Process Via “paper mills.” Available from: https://publicationethics.org/resources/forum-discussions/publishing-manipulation-paper-mills [Last accessed: February 15, 2023]. Google Scholar5. Nash J. Paper Mills—The Dark Side of the Academic Publishing Industry. MDPI Blog. Available from: https://blog.mdpi.com/2022/05/09/paper-mills/ [Last accessed: February 15, 2023]. Google ScholarFiguresReferencesRelatedDetails Volume 29Issue 3Mar 2023 InformationCopyright 2023, Mary Ann Liebert, Inc., publishersTo cite this article:Holger Cramer.Artificial Intelligence, Complementary and Integrative Medicine: A Paradigm Shift in Health Care Delivery and Research?.Journal of Integrative and Complementary Medicine.Mar 2023.131-133.http://doi.org/10.1089/jicm.2023.0040Published in Volume: 29 Issue 3: March 13, 2023PDF download