This paper is in the following e-collection/theme issue:

AI applications in genomics and pathology informatics, including ‘Generative AI’ (8) Machine Learning (1465) Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Artificial Intelligence (1371) Bioinformatics, genomics, tools and databases (17)

Published on in Vol 3, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/38226, first published .
The Application of Machine Learning in Predicting Mortality Risk in Patients With Severe Femoral Neck Fractures: Prediction Model Development Study

The Application of Machine Learning in Predicting Mortality Risk in Patients With Severe Femoral Neck Fractures: Prediction Model Development Study

The Application of Machine Learning in Predicting Mortality Risk in Patients With Severe Femoral Neck Fractures: Prediction Model Development Study

Authors of this article:

Lingxiao Xu1 Author Orcid Image ;   Jun Liu1 Author Orcid Image ;   Chunxia Han1 Author Orcid Image ;   Zisheng Ai1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Weng S, Lin D, Zeng J, Liu J, Zheng K, Chen P, Lin C, Lin F. Optimal sliding distance in femoral neck system for displaced femoral neck fractures: a retrospective cohort study. Journal of Orthopaedic Surgery and Research 2024;19(1) View