The Official Journal of the Turkish Society Of Clinical Microbiology and Infectious Diseases (KLİMİK)

Commentary

Using ChatGPT in the Medical Field: A Narrative

Ali Pekşen
×Affiliations
  • Publisher, Infectious Diseases and Clinical Microbiology
,
ChatGPT
×Affiliations
  • Generative Pre-trained Transformer, https://chat.openai.com/

This text was written by filtering the response of ChatGPT to our querries.

ChatGPT has jumped into many fields including the scientific arena. It seems that there could be benefits of this application, however there is a huge area that could be misused. We optimistically focused on the positive sides to inform our readers, and decided to ask ChatGPT to talk about itself.

 

ChatGPT (Generative Pre-trained Transformer) is a pre-trained language model developed by artificial intelligence (AI) research and deployment company OpenAI. It is based on the GPT architecture, which uses deep learning to generate human-like text. The model is trained on a large dataset of internet text and can be fine-tuned for a variety of language tasks, such as language translation, question answering, and text summarization.

The model can generate human-like text as what you are reading now and respond to the questions based on the given context. It is designed to generate text that is similar to text written by humans, and is capable of understanding context and generating responses that are appropriate to the conversation. 


What could be the Role of ChatGPT in the Medical Field?

One of the many fields that ChatGPT can be applied to is the medical field. The model can be fine-tuned to generate medical text, answer medical-related questions, provide recommendations for diagnosis and treatment, translate medical documents and even create a medical chatbot.

For instance, ChatGPT can be adjusted on a dataset of clinical notes, journal articles, and textbooks to generate more accurate and relevant medical text, which can be used in applications such as automated summarization of patient records and generating personalized treatment plans. Additionally, it can be regulated to answer medical-related questions, critical decision making which can be used in applications such as virtual medical assistants and chatbots to help patients find answers to their health-related questions. It can also be fine-tuned to analyze patient data and provide recommendations for diagnosis and treatment, which can be used in applications such as computer-aided diagnostic systems to help doctors make more informed decisions.

To use ChatGPT in the medical field, developers would need to obtain a large dataset of medical texts and fine-tune the model to the specific task they want to use it for. They would also need to have a good understanding of natural language processing and deep learning techniques to effectively implement and utilize the model.

How can we Benefit from ChatGPT While Writing Scientific Articles in the Medical Field? 

ChatGPT has several potential benefits for the process of writing scientific articles in the medical field. These include generating summaries of medical articles or clinical reports, completing incomplete sentences, paragraphs, or entire articles, translating medical articles from one language to another, correcting grammar and punctuation errors in medical articles, and searching for relevant literature based on keywords and phrases provided by the user.

To use ChatGPT for writing scientific articles in the medical field, authors would need to fine-tune the model on a large dataset of medical texts and have a good understanding of natural language processing and deep learning techniques.

ChatGPT is a powerful language model that can generate human-like text, but it is not capable of writing a complete scientific medical article on its own. The model is trained to generate text based on patterns it learned from the data it was trained on, and it is not capable of understanding the scientific process or conducting original research.

Is There a Role for ChatGPT in Medical Education?

ChatGPT has several potential uses for medical education, including generating educational content, creating virtual patient simulations, translating medical education materials, providing virtual tutoring, and automating grading. Fine-tuning ChatGPT to generate educational content can help educators create engaging and effective learning materials. ChatGPT can also generate virtual patient scenarios to help medical students practice their diagnostic and treatment skills. Language translation using ChatGPT can help educators and students learn and teach medical concepts in a language they are not proficient in. Virtual tutoring using ChatGPT can supplement classroom instruction and provide additional support for students who need extra help. Finally, automating grading using ChatGPT can save educators time while providing more accurate and detailed feedback to students.

What are the Limitations of ChatGPT ?

ChatGPT is a powerful language model that has some limitations. Firstly, it is trained on internet text which can contain biases and inaccuracies. Secondly, it does not have the ability to understand common sense reasoning and may generate nonsensical or irrelevant responses. Thirdly, its understanding of context is limited compared to that of a human’s, and it may not always generate appropriate or logical text. Fourthly, it is limited to text-based tasks and cannot handle other types of data. Fifthly, when using the GPT-3 API, there are limits on the number of requests and size of input, as well as costs involved. Finally, to get the best performance, fine-tuning of the model is required for specific tasks or domains.

Despite these limitations, ChatGPT is still a powerful tool for natural language processing and can be used to improve the performance of a wide range of language-based applications. It is important to be aware of its limitations and to use it in appropriate scenarios.

Can ChatGPT Write a Scientific Manuscript?

ChatGPT has been the subject of much discussion and debate among researchers, healthcare professionals, and publishers. While it has the potential to bring many benefits, there are also concerns about its accuracy, bias, data privacy, and impact on scientific publishing. One of the main concerns is the potential for inaccuracies and biases in the generated text, which is particularly important in medical settings where accuracy can be a matter of life and death. The use of patient data to train ChatGPT models also raises ethical concerns around privacy, confidentiality, and consent.

In addition, ChatGPT and other AI technologies have the potential to disrupt traditional scientific publishing models by automating parts of the writing and peer-review process. While this could lead to more efficient and faster publishing, it could also lead to lower quality and less rigorous scientific articles. There are also concerns about the potential for bias and plagiarism in AI-generated articles. All the institutional review boards and ethical committees should be awake against the misuse of ChatGPT. 

Despite these concerns, there are also potential benefits to using ChatGPT in the medical field and scientific article publishing. For example, it can help automate repetitive tasks, such as summarizing large amounts of data, generating patient care plans, and drafting sections of scientific articles. It can also reduce the time and effort required to write and review scientific articles, allowing researchers to focus on other aspects of their work.

In conclusion, while the use of ChatGPT in the medical field and scientific article publishing has the potential to bring many benefits, it is important to be mindful of the potential drawbacks and limitations of the technology. Careful consideration and ethical practices must be applied to ensure the accuracy, fairness, and ethical use of ChatGPT in these contexts.

Ethical Approval: N.A.

Informed Consent: N.A.

Peer-review: Externally peer-reviewed

Conflict of Interest: The author declares no conflict of interest.

Financial Disclosure: The author declared that this study has received no financial support.