Five-Year Life Expectancy Prediction of Prostate Cancer Patients Using Machine Learning Algorithms

Polash, Md. Shohidul Islam; Hossen, Shazzad; Haque, Aminul

doi:10.1007/978-3-031-27609-5_25

Cited by 1 publication

(1 citation statement)

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“…Ada Boost [32], Gradient descent, Stochastic Gradient Descent, Hist Gradient Boost, Light Gradient Boost, K-Nearest Neighbor, Naive Bayes, Logistic Regression, Bagging classifier, Multilayer Perceptron, Voting Classifier. The results of accuracy score, F1 score, recall, precision, AUC score [8], [18], [19], [25], [34], [35]- [37], etc., measurement have been used to analyze the model's performance. These performance measurements have been calculated with 20% of test data.…”

Section: E Models Creation and Results Analysismentioning

confidence: 99%

Survival Analysis of Thyroid Cancer Patients Using Machine Learning Algorithms

Alhashmi,

Polash,

Haque

et al. 2024

IEEE Access

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The medical community strives continually to improve the quality of care patients receive. Predictions of prognosis are essential for doctors and patients to choose a course of treatment. Recent years have witnessed the development of numerous new cancer survival prediction models. Most attempts to predict the prognosis of people with malignant growth rely on classification techniques. We could experiment with significantly different results using only a subset of SEER (Surveillance, Epidemiology, and End Results) data. These models were created using machine learning techniques by selecting univariate features and calculating correlations. We illustrated the variation in results and discrepancy of impurity that can result from varying data quantities and critical factors. Seventeen crucial factors were identified, and a group of classification algorithms were trained to evaluate the effectiveness of an estimation technique. In the display mode, the accuracy of these computations ranges from 97% to 99% Ȧlong with accuracy, the models are further evaluated regarding the F1 score, precision, recall, and the AUC score. Compared to earlier studies, a more accurate model has been developed, and, to the best of our knowledge, our prediction model is superior to the models studied in the previous works.

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