Title of article :
Diagnosing Lumbar Disc Operation with Data Science
Author/Authors :
Li ، Chang Faculty of Computer Science and Information System - Universiti Teknologi MARA (UiTM)
Abstract :
Lumbar disc operation is a common medical procedure that involves the removal of a herniated or damaged disc in the lower back. Accurate diagnosis of lumbar disc operation is crucial for effective treatment and management of the condition. In this paper, we propose a data science approach to diagnose lumbar disc operation using machine learning algorithms. We collected a dataset of patient records and used various data preprocessing techniques to clean and prepare the data. We then applied several machine learning algorithms to the dataset and evaluated their performance using various metrics. Our results show that our proposed approach can accurately diagnose lumbar disc operation with high accuracy and precision.
Keywords :
Lumbar Disc , Data Science , K , nearest neighbors algorithm , KNN , Diagnosing
Journal title :
International journal of industrial engineering and operational research
Journal title :
International journal of industrial engineering and operational research