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Updated: Jun 27, 2026

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants
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A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants

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预测母亲在前6个月的纯母乳养:使用机器学习技术创建接口的研究

Ayfer Açikgöz1, Merve Çakirli2, Berrak Mizrak Şahin3

  • 1Department of Child Health and Disease Nursing, Eskisehir Osmangazi University Health Sciences, Eskisehir, Turkey.

Journal of evaluation in clinical practice
|May 14, 2024
PubMed
概括

机器学习技术可以预测独家母乳养的成功. 关键因素包括母亲的健康,社会支持,水分,感知到的牛奶供应和婴儿养的便利性,使得有风险的母亲能够进行早期干预.

关键词:
母乳养 哺乳期 母乳养机器学习技术是机器学习技术.母亲的母亲们的母亲们预测模型 预测模型

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Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

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A Common Marmoset Model of Mother-Infant Intervention for Breastfeeding Disorders in the Presence of Paternal Inhibition and Maternal Neglect

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Development of Human Microbiota01:30

Development of Human Microbiota

The human microbiota begins developing at birth and undergoes continual change as we age. Infancy marks a critical period of microbial sensitivity, offering a “window of opportunity” during which beneficial microbes help mature the immune system. By age three, children typically develop a more stable and diverse microbial community. Newborns acquire microbes from their immediate environment; vaginal delivery favors maternal vaginal microbes, while cesarean births favor microbes from the skin...