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Call for papers - Current applications of predictive analytics in perioperative medicine

Guest Editors

Anahita Dabo-Trubelja, MD, FASA, Memorial Sloan Kettering Cancer Center, WCMC, USA
Lalit Gupta, MBBS, DA, DNB, MNAMS, Maulana Azad Medical College and Lok Nayak Hospital, India

Submission Status: Open   |   Submission Deadline: 30 January 2025


BMC Anesthesiology is calling for submissions to our Collection, Current applications of predictive analytics in perioperative medicine. This Collection highlights predictive techniques that are relevant to perioperative settings and evaluates real-world impact through clinical research, with a focus on leveraging predictive analytics for risk stratification and optimizing anesthesia delivery to improve patient outcomes. By surveying the latest techniques and applications, this Collection aims to demonstrate the value of predictive analytics for evidence-based, personalized perioperative care, ultimately informing efforts to improve patient outcomes.

Meet the Guest Editors

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Anahita Dabo-Trubelja, MD, FASA, Memorial Sloan Kettering Cancer Center, WCMC, USA

Dr Anahita Dabo-Trubelja has been on staff at Memorial Sloan Kettering as an attending anesthesiologist since 2002. She completed her residency at NYPH-Cornell Campus, followed by a fellowship in Critical Care Medicine at NYPH-Columbia Campus. Dr Dabo-Trubelja also holds NBE certifications in basic perioperative transesophageal echocardiography and critical care ultrasound. Her clinical care focuses on critical patients in the perioperative period and the use of echocardiography and point of care ultrasound (POCUS) as an adjunct to all aspects of patient care in the perioperative period. Dr Dabo-Trubelja’s academic interest focuses on promoting cancer anesthesia and research into ultrasound in cancer patients in the perioperative period. She is interested in the application of ultrasound as an adjunct to clinical assessment, decision making, and outcomes.

Lalit Gupta, MBBS, DA, DNB, MNAMS, Maulana Azad Medical College and Lok Nayak Hospital, India

Dr Lalit Gupta is a Professor in Anesthesiology and Intensive Care at Maulana Azad Medical College, New Delhi, with over 18 years of expertise. An accomplished author, he has contributed to over 120 publications in esteemed national and international journals and authored chapters in various books. Serving as "Editor" for numerous international and reputed journals, he is a Foundation member of the "Anaesthesia & Critical Care Foundation" society. Dr Gupta is a distinguished member of medical societies, including the National Academy of Medical Sciences, India, and actively contributes to conferences and educational initiatives globally. He has worked extensively on intensive care, palliative care and difficult airway management. He is also an instructor and provider for the Acute Critical Care Management course (ACCM).

About the Collection

BMC Anesthesiology is calling for submissions to our Collection, Current applications of predictive analytics in perioperative medicine. This Collection aims to examine contemporary applications of predictive analytics across perioperative care. With rising perioperative neurocognitive disorders (PNDs), predictive analytics shows promise for advancing risk assessment, monitoring, and management.

This Collection will highlight predictive techniques that are relevant to perioperative settings and evaluate real-world impact through clinical research, with a focus on  leveraging predictive analytics for risk stratification and optimizing anesthesia delivery to improve patient outcomes. Contributions should include perspectives from anesthesiologists, surgeons, data scientists, and other key stakeholders to align insights on the current and future landscape of predictive analytics in perioperative medicine. 

 Potential contributions can include, but are not limited to the following topics:

  • Forecasting surgical risks
  • Predicting complications 
  • Optimizing operating room schedules
  • Anticipating resource needs
  • Integrating predictive analytics into workflows


By surveying the latest techniques and applications, this Collection aims to demonstrate the value of predictive analytics for evidence-based, personalized perioperative care, ultimately informing efforts to improve patient outcomes.


Image credit: © greenbutterfly / Stock.adobe.com

There are currently no articles in this collection.

Submission Guidelines

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This Collection welcomes submission of original Research Articles. Review articles will be considered at the Editor’s discretion. Should you wish to submit a different article type, please read our submission guidelines to confirm that type is accepted by the journal. Articles for this Collection should be submitted via our submission system, Snapp. During the submission process you will be asked whether you are submitting to a Collection, please select "Current applications of predictive analytics in perioperative medicine" from the dropdown menu.

Articles will undergo the journal’s standard peer-review process and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

The Editors have no competing interests with the submissions which they handle through the peer review process. The peer review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.