Keywords
Logistic Regression
Hybrid algorithm
How to Cite
Abstract
The Soft tissue tumour detection based on machine learning involves using algorithms and models to identify and classify treatment tumours that arise in the Muscles, fat, nerves, and blood arteries are examples of soft tissues. In order to categorize soft tumours based on their histopathological features. We trained and tested both algorithms on a large dataset of histologically confirmed soft tissue tumours and achieved high accuracy, precision, and recall. Our results demonstrate the capacity of ML algorithms to enhance the precision and effectiveness of soft tissue tumour diagnosis and support clinical judgement. The performance of the hybrid algorithms in the classification of soft tissue tumours based on their histopathological features. The study found that both algorithms achieved high accuracy, precision, and recall rates, demonstrating the potential of ML algorithms to improve the accuracy and efficiency of soft tissue tumour diagnosis. The article provides valuable insights for pathologists and oncologists in the use of ML algorithms in soft tissue tumour diagnosis and clinical decision-makingReferences
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