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Prostate Cancer Probability Prediction By Machine Learning Technique.

Srđan Jović¹, Milica Miljković², Miljan Ivanović²

¹a Faculty of Technical Sciences , University of Priština , Kosovska Mitrovica , Serbia.

Cancer Investigation

|December 16, 2017

Summary

Machine learning techniques can predict prostate cancer, improving patient survival through early detection and tailored treatments. This study demonstrates the effectiveness of various machine learning models for accurate prostate cancer prediction.

Keywords:

Cancer Machine Learning Prediction Prostate

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Area of Science:

Oncology
Computer Science
Biomedical Engineering

Background:

Prostate cancer survival rates depend on early and accurate prediction.
Predictive models are crucial for developing effective, individualized treatment plans.
Machine learning offers powerful tools for developing sophisticated predictive models.

Purpose of the Study:

To investigate the efficacy of machine learning techniques for prostate cancer prediction.
To compare the performance of different machine learning algorithms in predicting prostate cancer.
To establish the potential of machine learning in improving prostate cancer patient outcomes.

Main Methods:

Application of several machine learning techniques.
Comparative analysis of the performance of selected algorithms.
Evaluation of prediction accuracy and clinical relevance.

Main Results:

Machine learning models showed significant potential in predicting prostate cancer.
Comparative analysis indicated varying performance levels among different techniques.
Results support the feasibility of using machine learning for clinical decision support.

Conclusions:

Machine learning techniques are viable tools for accurate prostate cancer prediction.
The study validates the use of machine learning to enhance patient survival probabilities.
Further research can refine these models for broader clinical application.