Conference Paper

Technological Trend Analysis for Surgical Operation Duration Estimation

Volume: 23 September 30, 2023
  • Ziya Karakaya *
  • Bahadır Tatar
EN

Technological Trend Analysis for Surgical Operation Duration Estimation

Abstract

Surgical procedures are complex in nature and operative time is subject to variability influenced by many factors. Accurate estimation of the surgical operation duration not only helps to maximize Operation rooms’ efficiency, but also helps to optimize hospital resources which are a crucial factor in planning surgical procedures. In this regard, Al techniques such as machine learning and deep learning promise to significantly improve the duration estimation by identifying hidden factors and make more accurate prediction. They achieve this success by identifying latent factors which are generally hard to be explored by human intelligence. Eventually, accuracy in time estimation added to a good scheduling optimization leads to make more efficient utilization of hospital resources by better aligning Operation Room, relevant equipment, and human resources. This study addresses the recent trends in research on surgical operations duration estimation, considering the relevant factors.

Keywords

References

  1. Abbas, A., Mosseri, J., Lex, J. R., Toor, J., Ravi, B., Khalil, E. B., & Whyne, C. (2022). Machine learning using preoperative patient factors can predict duration of surgery and length of stay for total knee arthroplasty. International Journal of Medical Informatics, 158. 104670.
  2. Bartek, M. A., Saxena, R. C., Solomon, S., Fong, C. T., Behara, L. D., Venigandla, R., Velagapudi, K., Lang, J. D., &Nair, B. G. (2019). Improving operating room efficiency: Machine learning approach to predict case-time duration. Journal of the American College of Surgeons, 229(4), 346–354.
  3. Bodenstedt, S., Wagner, M., Mündermann, L., Kenngott, H., Müller-Stich, B., Breucha, M., Mees, S. T., Weitz, J., & Speidel, S. (2019). Prediction of laparoscopic procedure duration using unlabeled, multimodal sensor data. International Journal of Computer Assisted Radiology and Surgery, 14, 1089-1095.

Details

Primary Language

English

Subjects

Environmental and Sustainable Processes

Journal Section

Conference Paper

Authors

Ziya Karakaya * This is me
Türkiye

Bahadır Tatar This is me
Türkiye

Early Pub Date

September 29, 2023

Publication Date

September 30, 2023

Submission Date

May 9, 2023

Acceptance Date

September 3, 2023

Published in Issue

Year 2023 Volume: 23

APA
Karakaya, Z., & Tatar, B. (2023). Technological Trend Analysis for Surgical Operation Duration Estimation. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 23, 349-360. https://doi.org/10.55549/epstem.1368277