DETECTION OF ORAL SQUAMOUS CELL CARCINOMA USING PRE-TRAINED DEEP LEARNING MODELS

The study successfully demonstrated the potential of using transfer learning-based methodologies in the medical field. The interpretation of the results suggests their practical viability and offers directions for future research aimed at improving diagnostic precision and serving as a reliable tool to physicians in the early diagnosis of cancer.

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Publication Details

Journal
Experimental Oncology
Published
2024-10-09
DOI
https://doi.org/10.15407/exp-oncology.2024.02.119
Citations
5
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
1.74
Controls
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article

DETECTION OF ORAL SQUAMOUS CELL CARCINOMA USING PRE-TRAINED DEEP LEARNING MODELS

Y. V. Lokeswari, Devendra Prasad, K. Dhanya
5 citations
Experimental Oncology
AI in cancer detection
1.74
article

DETECTION OF ORAL SQUAMOUS CELL CARCINOMA USING PRE-TRAINED DEEP LEARNING MODELS

Y. V. Lokeswari, Devendra Prasad, K. Dhanya
article en
5 citations

Abstract

The study successfully demonstrated the potential of using transfer learning-based methodologies in the medical field. The interpretation of the results suggests their practical viability and offers directions for future research aimed at improving diagnostic precision and serving as a reliable tool to physicians in the early diagnosis of cancer.

Experimental OncologyVol. 46(2)
Sri Sivasubramaniya Nadar College of Engineering (IN)
Openalex Percentile: Top 13%
AI in cancer detection
1.74
DOIOpen Access PDFOpenAlex
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DETECTION OF ORAL SQUAMOUS CELL CARCINOMA USING PRE-TRAINED DEEP LEARNING MODELS — Y. V. Lokeswari, Devendra Prasad, et al. · Experimental Oncology (2024) | TGRS Research Map | TGRS