AI in Health Care: Potential and Progress
Artificial Intelligence (AI) has the potential to transform health care and disrupt the field of medicine in significant ways. It has shown remarkable progress in tasks such as diagnostics, data analysis, and precision medicine and is already being applied in areas ranging from patient triage to cancer detection.
However, the recent availability of AI to the public, including language models like ChatGPT, has increased the awareness of AI and its potential capabilities in medicine. The continued growth of AI has spurred interest and debate concerning its broader use in patient care.
ChatGPT successfully passed the USMLE and can solve internal medicine case files, indicating its versatility and potential for future clinical applications. In fact, Google and DeepMind developed the Med-PaLM language model trained on several existing medical Q&A datasets to offer "safe and helpful answers" to questions posed by health care professionals and patients.
Language models, like ChatGPT and Med-PaLM, generate responses in a conversational manner to written statements, referred to as prompts, entered by users in a chat window. This is achieved without the need for coding, as the models utilize their training and data to generate contextually relevant responses.
In the near future, physicians may leverage medical-grade AI language models for consultations, receiving valuable insights and assistance in various aspects of patient care. We may even see prompts like the following become commonplace in health care:
- Provide advice on the diagnosis and treatment for these symptoms.
- Create a personalized treatment plan based on the patient's age and lifestyle.
- Analyze this X-ray to detect abnormalities.
- Identify risk factors from this patient's EHR.
- Write a letter explaining the medical necessity of this treatment.
By leveraging these powerful tools, doctors can improve the quality of care while saving time on tasks that can be automated with AI. With further development and refinement, AI technology could play an important role in enhancing the standard of care.
Physician-Machine Collaboration in Medicine
There is speculation about AI eventually replacing physicians, particularly in fields like radiology, pathology, and dermatology, where AI's diagnostic ability can match or even exceed that of clinicians. However, research suggests that physician-machine collaborations will outperform either one alone.
It's unlikely that AI will completely replace physicians anytime soon. The human aspects of care, including empathy, compassion, critical thinking, and complex decision-making, are invaluable in providing holistic patient care beyond diagnosis and treatment decisions.
I often ask participants in our digital transformation course if they would choose to have a serious medical diagnosis delivered by an AI trained to provide textbook empathy. Most participants would prefer to hear the news from a human doctor.
So, rather than fully replacing physicians, AI will likely empower the practice of medicine, with physicians leveraging the technology to enhance clinical care. To this point, the American Medical Association recommends that technology be used to augment, rather than replace, human intelligence.
AI also has the potential to address physician burnout by automating repetitive and monotonous administrative tasks, allowing physicians to focus on patient care. Moreover, AI could play a valuable role in improving access to care and addressing clinician workforce shortages.
As AI advances, physicians may be relied upon for higher-level decision-making, patient interaction, and interdisciplinary collaboration while working alongside AI systems.
Considerations of AI in Health Care
Despite the potential benefits of AI in health care, there are significant safety, privacy, reliability, and ethical considerations. Furthermore, without appropriate precautions, AI may perpetuate inherent biases in diagnosis and treatment.
Physicians will likely continue to play a critical role in ensuring that the ethical and moral implications of medical decisions are carefully considered and that patients receive the highest quality of care.
To achieve this, physicians must be prepared to take on new roles and responsibilities in the era of AI, including expanded opportunities in medical informatics. Physicians can also guide patients on how to use AI to obtain reliable health information and receive appropriate care.
Enhancing Medicine with AI
AI has the potential to transform health care for the better. It's a powerful tool that can lead to better patient outcomes when complemented with physician expertise. AI can also facilitate scientific discovery and breakthroughs in disease prevention and treatment through vast data analytics.
Integrating AI into routine clinical practice will require careful validation, training, and ongoing monitoring to ensure its accuracy, safety, and effectiveness in supporting physicians to deliver care.
While AI can be a valuable asset in the medical field, it cannot replace the human element. However, AI can and should be used to enhance the practice of medicine, empowering doctors with the latest technological tools to serve our patients better.
-
References
- Meskó B, Görög M. A short guide for medical professionals in the era of artificial intelligence. NPJ Digit Med. 2020 Sep 24;3:126. doi: 10.1038/s41746-020-00333-z. PMID: 33043150; PMCID: PMC7518439.
- Kung TH, Cheatham M, Medenilla A, Sillos C, De Leon L, Elepaño C, Madriaga M, Aggabao R, Diaz-Candido G, Maningo J, Tseng V. Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models. PLOS Digit Health. 2023 Feb 9;2(2):e0000198. doi: 10.1371/journal.pdig.0000198. PMID: 36812645; PMCID: PMC9931230.
- Lee P, Bubeck S, Petro J. Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine. N Engl J Med. 2023 Mar 30;388(13):1233-1239. doi: 10.1056/NEJMsr2214184. PMID: 36988602.
- Haug CJ, Drazen JM. Artificial Intelligence and Machine Learning in Clinical Medicine, 2023. N Engl J Med. 2023 Mar 30;388(13):1201-1208. doi: 10.1056/NEJMra2302038. PMID: 36988595.