Bartosz Machura, Damian Kucharski, Oskar Bozek, Bartosz Eksner, Bartosz Kokoszka, Tomasz Pekala, Mateusz Radom, Marek Strzelczak, Lukasz Zarudzki, Benjamín Gutiérrez-Becker, Agata Krason, Jean Tessier, Jakub Nalepa
Deep learning ensembles for detecting brain metastases in longitudinal multi-modal MRI studies
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
articles objectives develop model predict childrens recovery elbow function following supracondylar fracture analyze risk factors affecting childrens elbow function surgery propose individualized treatment strategy elbow function various children retrospectively analyzed clinical data 410 children supracondylar humerus fracture modeling set validation set kids included studies arbitrarily split 2 groups 73 basis identify statistically significant risk factors univariate logistic regression analysis used multivariate logistic regression used risk factors best logistic regression model chosen based sensitivity accuracy create nomogram total 410 children included study according inclusion criteria among 248 males 162 females fracture type 147 cases type iib 263 cases type iii significant changes afflicted limbs lateral difference surgical method onset season number kwires according univariate logistic regression analysis age p 001 weight p 001 height p 001 preoperative elbow soft tissue injury 1724 95 ci 10402859 p 035 sex 2220 95 ci 12993794 p 004 fracture classification gartland iib 0252 95 ci 01490426 p 001 nerve injury surgery 0304 95 ci 01550596 p 001 prying technique 0464 95 ci 02340920 p 028 postoperative daily light time 2 hours 0488 95 ci 02490955 p 036 significant difference univariate analysis multivariate regression analysis yielded independent risk factors fracture classification nerve injury surgery daily light duration surgery 2 hours soft tissue injury age postoperative cast fixation time establishment predictive model significance pediatric orthopedic clinicians daily diagnosis treatment supracondylar humerus fracture