The concept involves analyzing medical data related to kids, their allergies, and associated risk factors. This data could include symptoms, environmental conditions, family history, and other relevant information. The model learns to represent this data using word embeddings, effectively transforming the raw information into a numerical format that can be processed by the machine learning or deep learning algorithms. With KARATE, we can automate the assessment of allergy risks in children based on their profiles, helping healthcare professionals make informed decisions and providing parents with valuable insights into potential allergic reactions their kids might face. This model could prove to be a valuable tool in pediatric care, especially when dealing with common allergies and potential health risks in children.


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Year / 歲
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KG / 公斤
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CM / 公分
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Year / 歲
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KU/L
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ng/mL
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ng/mL
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μg/mL
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ppb
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ng/mL
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