Image 2_Development and application of machine learning models for hematological disease diagnosis using routine laboratory parameters: a user-friendly diagnostic platform.jpeg

Image 2_Development and application of machine learning models for hematological disease diagnosis using routine laboratory parameters: a user-friendly diagnostic platform.jpeg

Aim<p>In recent years, with the change of social environment, the incidence and detection rate of hematological diseases have shown an increasing trend. Early diagnosis and detection of hematological diseases are very important to improve the quality of life and prognosis of patients.</p>...

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Main Author: Jingya Liu (13338460) (author)
Other Authors: Yang Gou (22346113) (author), Wuchen Yang (11606577) (author), Hao Wang (39217) (author), Jing Zhang (23775) (author), Shengwang Wu (22346116) (author), Siheng Liu (22346119) (author), Tinglu Tao (22346122) (author), Yongjie Tang (11828551) (author), Cheng Yang (273624) (author), Siyin Chen (11638942) (author), Ping Wang (42415) (author), Yimei Feng (6383840) (author), Cheng Zhang (70708) (author), Shuiqing Liu (2826422) (author), Xiangui Peng (9138497) (author), Xi Zhang (83736) (author)
Published: 2025
Subjects:
Foetal Development and Medicine
hematological diseases
machine learning
prediction model
SHAP
laboratory parameters
diagnostic platform
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