# Assessment and Recurrence of Kidney Stones Through Optimized Machine Learning Tree Classifiers Using Dietary Water Quality Parameters and Patient’s History

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/assessment-and-recurrence-of-kidney-stones-through-optimized-machine-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | B. Kavitha,P. Parthiban,Mukesh Goel,K. Ravikumar,Amit Kumar Das,J. S. Sudarsan,S. Nithiyanantham |
| Citations | 3 |
| DOI | 10.1166/asem.2020.2681 |
| Fields | Medicine |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W3201302734 |
| Type | article |
| Year | 2020 |

## Paper authors

- [B. Kavitha](https://scholariq.org/researchers/b-kavitha/)

## Paper journal

- [Advanced Science Engineering and Medicine](https://scholariq.org/journals/advanced-science-engineering-and-medicine/)

## Paper primary topic

- [Kidney Stones and Urolithiasis Treatments](https://scholariq.org/topics/kidney-stones-and-urolithiasis-treatments/)

## Paper topics

- [Kidney Stones and Urolithiasis Treatments](https://scholariq.org/topics/kidney-stones-and-urolithiasis-treatments/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.