Predicting breast cancer 5-year survival using machine learning: A systematic review
J Li, Z Zhou, J Dong, Y Fu, Y Li, Z Luan, X Peng - PloS one, 2021 - journals.plos.org
Background Accurately predicting the survival rate of breast cancer patients is a major issue
for cancer researchers. Machine learning (ML) has attracted much attention with the hope …
for cancer researchers. Machine learning (ML) has attracted much attention with the hope …
Safety leading indicators for construction sites: A machine learning approach
CQX Poh, CU Ubeynarayana, YM Goh - Automation in construction, 2018 - Elsevier
The construction industry is one of the most dangerous industries in many countries. To
improve the situation, senior managers overseeing portfolios of construction projects need to …
improve the situation, senior managers overseeing portfolios of construction projects need to …
Machine-learning-based patient-specific prediction models for knee osteoarthritis
A Jamshidi, JP Pelletier, J Martel-Pelletier - Nature Reviews …, 2019 - nature.com
Osteoarthritis (OA) is an extremely common musculoskeletal disease. However, current
guidelines are not well suited for diagnosing patients in the early stages of disease and do …
guidelines are not well suited for diagnosing patients in the early stages of disease and do …
Effective prediction of three common diseases by combining SMOTE with Tomek links technique for imbalanced medical data
Diabetes, vertebral column pathologies and Parkinson's disease are three common
diseases which have high prevalence and brought great trouble and pain to billions of …
diseases which have high prevalence and brought great trouble and pain to billions of …
[HTML][HTML] Data mining and machine learning in cancer survival research: an overview and future recommendations
I Kaur, MN Doja, T Ahmad - Journal of Biomedical Informatics, 2022 - Elsevier
Data mining and machine learning techniques are transforming the decision-making
process in the medical world. From using nomograms and expert advice, scientists are now …
process in the medical world. From using nomograms and expert advice, scientists are now …
Joint use of over-and under-sampling techniques and cross-validation for the development and assessment of prediction models
R Blagus, L Lusa - BMC bioinformatics, 2015 - Springer
Background Prediction models are used in clinical research to develop rules that can be
used to accurately predict the outcome of the patients based on some of their characteristics …
used to accurately predict the outcome of the patients based on some of their characteristics …
A comparative analysis of deep learning approaches for predicting breast cancer survivability
Breast cancer is the second largest cause of mortality among women. Breast cancer patients
in developed nations have a relative survival rate of more than 5-years due to early …
in developed nations have a relative survival rate of more than 5-years due to early …
SMOTE for handling imbalanced data problem: A review
Imbalanced class data distribution occurs when the number of examples representing one
class is much lower than others. This conditioning affects the prediction accuracy degraded …
class is much lower than others. This conditioning affects the prediction accuracy degraded …
Machine learning (ML) techniques to predict breast cancer in imbalanced datasets: a systematic review
A Ghavidel, P Pazos - Journal of Cancer Survivorship, 2023 - Springer
Abstract Knowledge discovery in databases (KDD) is crucial in analyzing data to extract
valuable insights. In medical outcome prediction, KDD is increasingly applied, particularly in …
valuable insights. In medical outcome prediction, KDD is increasingly applied, particularly in …