1型糖尿病的新生儿和出生风险因素:使用人工神经网络进行预测
Claudiu Cobuz1, Mădălina Ungureanu-Iuga2, Maricela Cobuz1,3
1Faculty of Medicine and Biological Sciences, Ştefan cel Mare University of Suceava, 13th Universităţii Street, 720229 Suceava, Romania.
Life (Basel, Switzerland)
|December 30, 2025
概括
新生儿和周围产生的因素,如出生体重和养类型影响1型糖尿病 (T1D) 风险. 预测模型对早期T1D诊断和管理充满希望.
科学领域:
- 儿科 儿科 儿科
- 内分泌学 在内分泌学.
- 数据科学数据科学数据科学
背景情况:
- 1型糖尿病 (T1D) 是一种复杂的自身免疫性疾病,可能与早期的环境因素有关.
- 了解新生儿和围产期影响对于识别风险人群至关重要.
研究的目的:
- 调查新生儿和围产期因素对T1D风险的影响.
- 评估T1D风险评估预测模型的有效性.
主要方法:
- 使用相关性,通用线性模型 (GLM) 和人工神经网络 (ANN) 对327名患者队列的分析.
- 研究的关键因素包括Apgar分数,出生体重,养类型,性别和分娩类型.
主要成果:
- 一型糖尿病患者的出生体重较高,阿巴格分数较低,配方奶粉的患病率较高,剖腹产增加.
- GLM将营养类型,出生体重和Apgar分数确定为重要的预测因素 (R2 = 0.88).
- 在区分风险方面,ANN表现出高准确度 (84.2%),AUC (0.95),灵敏度 (89.1%) 和特异性 (76.7%).
结论:
- 生命早期的因素与T1D风险有显著的相关性,并确定了复杂的相互作用.
- 开发的预测模型,特别是ANN,显示出早期T1D诊断和个性化管理的巨大潜力.
- 建议对更大,独立的数据集进行进一步验证,以确认预测性能.
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