Call for Papers Special Issue in Jordan Medical Journal "Evaluating Generative AI-Based Models in Healthcare"

2024-01-18

 

Call for Papers

Special Issue in Jordan Medical Journal

"Evaluating Generative AI-Based Models in Healthcare "

Special Issue Editors

  • Professor Dr. Dr. Jan Egger

Institute for Artiicial Intelligence in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, Essen, Germany.

E-mail: jan.egger@uk-essen.de 

  • Malik Sallam, M.D., Ph.D.

Department of Pathology, Microbiology, and Forensic Medicine – the School of

Medicine – The University of Jordan. Department of Clinical Laboratories and

Forensic Medicine – Jordan University Hospital. Department of Translational

Medicine – Faculty of Medicine – Lund University. E-mail: malik.sallam@ju.edu.jo 

 

Special Issue Information

Dear colleagues,

Large language models (LLMs) gained popularity particularly for ChatGPT publicly released by OpenAI a year ago. Other popular conversational chatbots include Bing by Microsoft and Bard by Google.

Since then, an extensive number of studies investigated the potential of these models in various aspects in healthcare education, research, and practice with variable results and conclusions. A major limitation of these studies was the lack of standardization in design and reporting of the indings. In this special issue, we would welcome submissions using the standardized assessment of AI models in healthcare education, research, and practice using the CLEAR-METRICS approach.

This approach involves the design and reporting of AI assessment studies using the METRICS checklist. Additionally, the evaluation of the AI models’ output can beneit from an assessment tool speciically designed for this purpose and referred to as “CLEAR”. We encourage the authors to submit the full data in a publicly available free data repository.

This Special Issue in the Jordan Medical Journal (JMJ) will focus on studies addressing the performance of these AI-based models in various aspects of healthcare education, research, and practice.

The manuscripts will undergo an editorial evaluation in a maximum of 48 hours, and if the quality is suitable, peer review will ensue. The accepted manuscripts will be published ahead-of-print. The editorial policy at JMJ is outlined at: https://jjournals.ju.edu.jo/index.php/JMJ/EditorialPolicy For submissions from authors with conlict of interest with both guest editors, the submission would be handled directly by JMJ Editor-in-Chief, Prof. Dr. Malik E. Juweid Beneits of submission:

  • Free publishing in an open access journal indexed in Scopus database by Elsevier.
  • Free language editing service.
  • Expedited editorial evaluation (maximum of 48 hours) and expedited peer review (maximum of 2 weeks).
  • Freely available style of preparing the manuscript and for referencing.

Scopus coverage years: from 1972 to 1978, from 1980 to 1982, from 1984 to 1986, from 1988 to 1991, from 2006 to Present.

Publisher: The University of Jordan; Subject area: “Medicine: General Medicine” https://www.scopus.com/sourceid/15332

Keywords

  • ChatGPT
  • Bing
  • Bard
  • Healthcare education
  • Healthcare practice
  • Healthcare research
  • AI in healthcare
  • Generative AI

Timeline

  • Submission opens from 24 January 2024
  • Submission closes on 30 November 2024
  • The accepted manuscripts will be published and indexed ahead-of-print alongside the regular issues, and they will also be assigned to the special issue number S1.

 

References

  • Sallam M: ChatGPT Utility in Healthcare Education, Research, and Practice: Systematic Review on the Promising Perspectives and Valid Concerns. Healthcare (Basel). 2023, 11:887. doi: 10.3390/healthcare11060887
  • Li J, Dada A, Kleesiek J, Egger J: ChatGPT in Healthcare: A Taxonomy and Systematic Review. medRxiv. 2023:2023.2003.2030.23287899. doi: 10.1101/2023.03.30.23287899
  • Sallam M, Barakat M, Sallam M: METRICS: Establishing a Preliminary Checklist to Standardize Design and Reporting of Artificial Intelligence-Based Studies in Healthcare. JMIR Preprints. 2023. doi: 10.2196/preprints.54704
  • Sallam M, Barakat M, Sallam M: Pilot Testing of a Tool to Standardize the Assessment of the Quality of Health Information Generated by Artificial Intelligence-Based Models. Cureus. 2023, 15:e49373. doi: 10.7759/cureus.49373
  • Meskó B: Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial. J Med Internet Res. 2023, 25:e50638. doi: 10.2196/50638
  • Puladi B, Gsaxner C, Kleesiek J, Hölzle F, Röhrig R, Egger J: The impact and opportunities of large language models like ChatGPT in oral and maxillofacial surgery: a narrative review. Int J Oral Maxillofac Surg. 2023, Epub ahead of print. doi: 10.1016/j.ijom.2023.09.005
  • Bajwa J, Munir U, Nori A, Williams B: Artificial intelligence in healthcare: transforming the practice of medicine. Future Healthc J. 2021, 8:e188-e194. doi: 10.7861/fhj.2021-0095
  • Kleesiek J, Wu Y, Stiglic G, Egger, J, Bian, J: An Opinion on ChatGPT in Health Care-Written by Humans Only. Journal of Nuclear Medicine. 2023, 64:701-703. doi: 10.2967/jnumed.123.265687

 

 

 

We are looking forward to your contribution.

Guest Editors

Prof. Dr. Jan Egger

Dr. Malik Sallam