# Quantitative Analysis of Benign and Malignant Tumors in Histopathology: Predicting Prostate Cancer Grading Using SVM

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/quantitative-analysis-of-benign-and-malignant-tumors-in-histopathology/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Subrata Bhattacharjee,Hyeon‐Gyun Park,Cho‐Hee Kim,Deekshitha Prakash,Nuwan Madusanka,Jae-Hong So,Nam-Hoon Cho,Heung‐Kook Choi |
| Citations | 40 |
| DOI | 10.3390/app9152969 |
| Fields | Computer Science,Engineering,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://www.mdpi.com/2076-3417/9/15/2969/pdf |
| OpenAlex ID | https://openalex.org/W2964088022 |
| Type | article |
| Year | 2019 |

## Paper authors

- [Nuwan Madusanka](https://scholariq.org/researchers/nuwan-madusanka/)

## Paper journal

- [Applied Sciences](https://scholariq.org/journals/applied-sciences/)

## Paper primary topic

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)

## Paper topics

- [AI in cancer detection](https://scholariq.org/topics/ai-in-cancer-detection/)
- [Radiomics and Machine Learning in Medical Imaging](https://scholariq.org/topics/radiomics-and-machine-learning-in-medical-imaging/)
- [Medical Imaging and Analysis](https://scholariq.org/topics/medical-imaging-and-analysis/)

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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.