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Updated: May 25, 2025

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开发和验证一种机器学习方法来选新的麻风病例,该方法基于麻风病嫌疑问卷问卷

Mateus Mendonça Ramos Simões1,2, Filipe Rocha Lima1,2,3, Helena Barbosa Lugão1,2

  • 1Dermatology Division, Department of Internal Medicine, National Referral Center for Sanitary Dermatology and Hansen's Disease, Clinical Hospital of the Ribeirão Preto Medical School, University of São Paulo, São Paulo, Brazil.

Scientific reports
|February 26, 2025
PubMed
概括

一个新的机器学习工具,MaLeSQs,有助于积极寻找麻风病例. 它识别了需要进一步评估的个体,改善了对这种神经损伤性疾病的早期发现.

关键词:
积极搜索 积极搜索这是大麻风病.麻风病怀疑调查问卷 麻风病怀疑问卷机器学习是机器学习.查检查 查检查 查检查

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In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
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