CLINICAL PREDICTIVE MODEL USING MACHINE LEARNING - Ravi Shekhar,Ashutosh Kumar,Mohammad Zeeshan
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Piegāde 12-18 darba dienu laikā
30 dienu atgriešanas politika
In the healthcare industry, big data analytics is extremely important, evidently since the industry itself is home to a vast sea of datasets. Analytics is used to examine these datasets and uncover hidden information and trends in order to extract knowledge and anticipate outcomes. The current existing approaches lack considerable categorization and prediction accuracy since the fetching of structured healt ... Pilns apraksts
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Aprašymas
In the healthcare industry, big data analytics is extremely important, evidently since the industry itself is home to a vast sea of datasets. Analytics is used to examine these datasets and uncover hidden information and trends in order to extract knowledge and anticipate outcomes. The current existing approaches lack considerable categorization and prediction accuracy since the fetching of structured healthcare and clinical data is time-consuming and accurate prediction of diseases using real-time reports is a tough and computationally intensive task. Therefore, understanding motives behind machine learning approaches in healthcare are essential, since precision and accuracy are often critical in healthcare problems. The aims is to build a generalized clinical machine learning predictive model using supervised classification algorithms, in-order to predict various common yet severe health diseases through a binary output.
Vairāk informācijas
| Autors | Ravi Shekhar, Ashutosh Kumar, Mohammad Zeeshan |
|---|---|
| Izdevējs | LAP LAMBERT Academic Publishing |
| Izlaides gads | 2022 |
| Vāka tips | Mīkstais vāks |
| EAN | 9786205517093 |