Development and validation of an interpretable machine learning model for predicting Philadelphia chromosome-positive acute lymphoblastic leukaemia using clinical and laboratory parameters: a single-centre retrospective study

Development and validation of an interpretable machine learning model for predicting Philadelphia chromosome-positive acute lymphoblastic leukaemia using clinical and laboratory parameters: a single-centre retrospective study

Objective To develop and validate a prediction model of Philadelphia chromosome-positive acute lymphoblastic leukaemia (Ph+ALL).Design A single-centre retrospective study.Participants This study analysed 471 newly diagnosed patients with ALL at the Second Affiliated Hospital of Army Medical Universi...

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Bibliographic Details
Main Authors: Jing Zhang, Cheng Zhang, Xi Zhang, Wuchen Yang, Jingya Liu, Yang Gou, Xingqin Huang, Maoshan Chen, Dezhi Huang, Shengwang Wu, Shuiqing Liu, Xiangui Peng
Format: Article
Language:English
Published: BMJ Publishing Group 2025-06-01
Series:BMJ Open
Online Access:https://bmjopen.bmj.com/content/15/6/e097526.full
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