Development of a Machine Learning Model to Predict Early Ambulation after Proximal Femoral Fracture Surgery

Authors

Institutions

Publication Details

Journal
The Japanese Journal of Rehabilitation Medicine
Published
2026-02-17
DOI
https://doi.org/10.2490/jjrmc.25010
Primary Topic
Hip and Femur Fractures
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development of a Machine Learning Model to Predict Early Ambulation after Proximal Femoral Fracture Surgery

Junko Mizutani, Shu Akiba, Tetsuya Katakura, Chinatsu Kutsuma et al.
The Japanese Journal of Rehabilitation Medicine
Hip and Femur Fractures
article

Development of a Machine Learning Model to Predict Early Ambulation after Proximal Femoral Fracture Surgery

Junko Mizutani, Shu Akiba, Tetsuya Katakura, Chinatsu Kutsuma, Mei Amano
article en

Abstract

No abstract available for this paper.
The Japanese Journal of Rehabilitation Medicine
Saiseikai Central Hospital (JP)
Openalex Percentile: Top 52%
Hip and Femur Fractures
DOISourceOpenAlex
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Development of a Machine Learning Model to Predict Early Ambulation after Proximal Femoral Fracture Surgery — Junko Mizutani, Shu Akiba, et al. · The Japanese Journal of Rehabilitation Medicine (2026) | TGRS Research Map | TGRS