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Grafico della conoscenza per il motore decisionale
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ISBN10: 6207696077
ISBN13: 9786207696079
Publisher: Edizioni Sapienza
Published: Jun 24 2024
Pages: 52
Weight: 0.20
Height: 0.12 Width: 6.00 Depth: 9.00
Language: Italian
ISBN13: 9786207696079
Publisher: Edizioni Sapienza
Published: Jun 24 2024
Pages: 52
Weight: 0.20
Height: 0.12 Width: 6.00 Depth: 9.00
Language: Italian
Con l'avvento delle tecnologie Bigdata, i dati sanitari vengono acquisiti e archiviati a più livelli granulari e in più formati. Nel settore sanitario, gli ospedali, le aziende farmaceutiche e le compagnie assicurative dispongono di un'enorme quantità di dati in tabelle strutturate. Tuttavia, quantità significative di big data rimangono sottoutilizzate a causa dell'isolamento, della distribuzione e dell'eterogeneità dei dati. Nonostante l'interconnessione di dati tabellari collegati tra loro in qualche modo per l'input di ML, le sfide sono: aumento della dimensionalità , normalizzazione dei dati che non sono una rappresentazione naturale, ripetizione dei dati nell'unione di diversi dati aggregati tra le tabelle. I modelli di apprendimento automatico suppongono che le osservazioni non siano dipendenti, ma le informazioni del mondo reale sono interconnesse. I grafi della conoscenza e l'apprendimento automatico sono due strumenti importanti per comprendere e modellare concetti complessi, mentre l'apprendimento automatico è un processo attraverso il quale i computer imparano dai dati, senza essere esplicitamente programmati.
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