Artificial intelligence for predicting 30-day mortality after surgery for femoral shaft fractures: A retrospective study

This study is the first to internally validate an AI-driven model for predicting mortality within 30 days of surgery in an isolated population of femoral shaft fracture patients, demonstrating good performance. Further research is needed to develop an excellent-performing, AI-driven model that is externally validated prior to clinical translation to support anaesthesiologists and orthopaedic surgeons in perioperative risk stratification and patient education.

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Publication Details

Journal
Indian Journal of Anaesthesia
Published
2025-05-14
DOI
https://doi.org/10.4103/ija.ija_1060_24
Citations
6
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.93
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article

Artificial intelligence for predicting 30-day mortality after surgery for femoral shaft fractures: A retrospective study

Rameshbabu Manyam, Kunj Patel, Eric Heinz, Puneet Gupta et al.
6 citations
Indian Journal of Anaesthesia
Artificial Intelligence in Healthcare and Education
3.93
article

Artificial intelligence for predicting 30-day mortality after surgery for femoral shaft fractures: A retrospective study

Rameshbabu Manyam, Kunj Patel, Eric Heinz, Puneet Gupta, Rui Guo, Hong-Jui Shen
article en
6 citations

Abstract

This study is the first to internally validate an AI-driven model for predicting mortality within 30 days of surgery in an isolated population of femoral shaft fracture patients, demonstrating good performance. Further research is needed to develop an excellent-performing, AI-driven model that is externally validated prior to clinical translation to support anaesthesiologists and orthopaedic surgeons in perioperative risk stratification and patient education.

Indian Journal of AnaesthesiaVol. 69(6)
Emory University (US), George Washington University (US)
Openalex Percentile: Top 6%
Artificial Intelligence in Healthcare and Education
3.93
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