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    • Additional File 5 of Patient-level Performance Evaluation of a Smartphone-Based Malaria Diagnostic Application

    Hang Yu, Fayad O. Mohammed,Feng Yang,Yasmin M. Kassim, Abdelrahim Mohamed,Richard J. Maude,Xavier C. Ding,Ewurama D.A. Owusu,Seda Yerlikaya,Sabine Dittrich,Stefan Jaeger

    Figshare（2023）

    California Institute of Technology | University of Khartoum | Guangxi Medical University | United States National Library of Medicine | Mahidol University | Foundation for Innovative New Diagnostics

    Cited 0|Views1
    Abstract
    Additional file 5: Object_score_histograms.zip: Object score histograms for each patient.
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    • Pretraining has recently greatly promoted the development of natural language processing (NLP)
    • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
    • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
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    【要点】：本文研究了基于智能手机的疟疾诊断应用程序在患者层面的性能评估，提出了一个创新性的诊断方法，并详细分析了诊断结果的分布。
    

    【方法】：作者使用了一种基于智能手机的图像识别技术，通过分析疟疾寄生虫的显微图像来进行疟疾诊断。
    

    【实验】：研究者在实验中使用了患者的疟疾寄生虫图像数据集，具体数据集名称未提及，通过实验得出了每个患者的对象得分直方图，用以评估诊断性能。