A hybrid machine learning model for timely prediction of breast cancer

S Dalal, EM Onyema, P Kumar… - … Journal of Modeling …, 2023 - World Scientific
Breast cancer is one of the leading causes of untimely deaths among women in various
countries across the world. This can be attributed to many factors including late detection …

A review of cancer data fusion methods based on deep learning

Y Zhao, X Li, C Zhou, H Pen, Z Zheng, J Chen, W Ding - Information Fusion, 2024 - Elsevier
With advancements in modern medical technology, an increasing amount of cancer-related
information can be acquired through various means, such as genomics, proteomics …

[HTML][HTML] Health-Related Quality of Life Scores and Values as Predictors of Mortality: A Scoping Review

AG Nevarez-Flores, KJ Chappell, VA Morgan… - Journal of General …, 2023 - Springer
Health-related quality of life (HRQoL) can be assessed through measures that can be
generic or disease specific, encompass several independent scales, or employ holistic …

[HTML][HTML] Evaluation of machine learning algorithms for the prognosis of breast cancer from the Surveillance, Epidemiology, and End Results database

R Wu, J Luo, H Wan, H Zhang, Y Yuan, H Hu, J Feng… - Plos one, 2023 - journals.plos.org
Introduction Many researchers used machine learning (ML) to predict the prognosis of
breast cancer (BC) patients and noticed that the ML model had good individualized …

A non-linear time series based artificial intelligence model to predict outcome in cardiac surgery

S Konar, N Auluck, R Ganesan, AK Goyal, T Kaur… - Health and …, 2022 - Springer
Background Adverse lifestyles have led to increased cardiac complications, further
accelerating the burden of cardiac surgeries in tertiary care hospitals. For optimum …

[PDF][PDF] Survival Prediction with Extreme Learning Machine, Supervised Principal Components and Regularized Cox Models in High-Dimensional Survival Data by …

F CANTAS TURKIS, I KURT OMURLU… - Gazi University Journal …, 2024 - researchgate.net
Along with the developing technology, it has become easier to collect data and store it,
which causes an increase in the number of data dimensions. The number of dimensions …

[PDF][PDF] Using Machine Learning to Predict the Future Fatigue of Patients with Colorectal Cancer, Endometrial Cancer, Ovarian Cancer, and Multiple Lymphoma Types

D Adiprakoso - 2023 - essay.utwente.nl
Methods This study created prediction models predicting the presence of clinically relevant
fatigue after 24 to 36 months (classification) and predicting the change in fatigue for a patient …

Yüksek Boyutlu Sağkalım Verilerinin Denetimli Temel Bileşenler, Cezalı Cox Regresyon ve Aşırı Öğrenme Makineleri Yöntemleri ile Karşılaştırmalı Analizi

F Cantaş Türkiş - 2022 - adudspace.adu.edu.tr
Amaç: Bu çalışmanın amacı farklı sansür oranlarına göre türetilen yüksek boyutlu sağkalım
verilerinde aşırı öğrenme makineleri tabanlı sağkalım modelleri, denetimli temel bileşenler …

Survival Prediction with Extreme Learning Machine, Supervised Principal Components and Regularized Cox Models in High-Dimensional Survival Data by Simulation

FC Türkiş, İK Omurlu, M Türe - Gazi University Journal of Science - dergipark.org.tr
Mortality risks of important diseases such as cancer can be estimated using gene profiles
which are high-dimensional data obtained from gene expression sequences. However, it is …