The Application of Large Language Models in Clinical Practice

Dear Colleagues,

Large language models (LLMs) now make it possible to accelerate advances in medical practice by making it easier to deploy advanced natural language processing methods for a wide range of challenges. LLMs can help find connections between large and disparate sources of information, including patient data, medical literature, and other underutilized sources of information, such as national census data. LLMs can also allow clinicians to access summary information drawn from disparate clinical notes, including progress notes, consultation notes, discharge summaries, referral notes, and SOAP notes.

This Special Issue aims to bring together researchers and practitioners working in the areas of natural language processing and clinical applications of deep learning and their assessment. We welcome original research articles that report on novel and significant findings in the following areas:

• Medical, nursing, and community health worker supporting applications of large language models.
• Diagnostics, e.g., methods for identifying diseases, recommending treatments, or predicting patient risks and outcomes.
• Streamlining clinical workflows.
• Summarization and de-identification of clinical notes.
• Ethical considerations and mitigation strategies for addressing bias when using LLM.

We welcome original and unpublished research articles that report on innovative and significant research findings related to the application of large language models in clinical practice. We only accept full-length research articles for this Special Issue, and we encourage authors to follow the standard research paper format and provide a clear and concise description of their research findings.

This Special Issue aims to present cutting-edge research in the field of large language model applications in clinical practice. We welcome high-quality research papers that report on novel and significant research findings that contribute to improved patient outcomes or our understanding of them. We look forward to receiving your submissions and making this Special Issue a success.

Prof. Dr. Susan McRoy
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. BioMedInformatics is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• applications of large language models
• user studies or evaluations
• clinical decision support
• diagnostics
• summarization
• de-identification
• ethical considerations and mitigation strategies when using LLM