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Machine Learning Explainability in Breast Cancer Survival

Tom Jansen, Gijs Geleijnse, Marissa Van Maaren, Mathijs P Hendriks, Annette Ten Teije, Arturo Moncada-Torres
2020 Studies in Health Technology and Informatics  
In this paper, we used data from the Netherlands Cancer Registry to generate a ML-based model to predict 10-year overall survival of breast cancer patients.  ...  Machine Learning (ML) can improve the diagnosis, treatment decisions, and understanding of cancer.  ...  Jansen et al. / Machine Learning Explainability in Breast Cancer Survival  ... 
doi:10.3233/shti200172 pmid:32570396 fatcat:ewjcsphrwrbxdaxgesx6xbwifq

An Artificial Intelligence-Enabled Pipeline for Medical Domain: Malaysian Breast Cancer Survivorship Cohort as a Case Study

Mogana Darshini Ganggayah, Sarinder Kaur Dhillon, Tania Islam, Foad Kalhor, Teh Chean Chiang, Elham Yousef Kalafi, Nur Aishah Taib
2021 Diagnostics  
The pipeline proposed in this study is a one-stop center to manage data, to automate analytics using machine learning, to automate scoring and to produce explainable interactive visuals to enhance clinician-patient  ...  A case study of breast cancer survival cohort from the University Malaya Medical Centre was used to develop and evaluate the pipeline.  ...  The authors also thank each and every one who has contributed their time and ideas to accomplish the pipeline presented in this study.  ... 
doi:10.3390/diagnostics11081492 fatcat:mq6nrg3hu5c7rpyqjgrlvol3q4

"Machine Learning Analysis of a Chilean Breast Cancer Registry"

Cesar Sánchez
2021 Biomedical Journal of Scientific & Technical Research  
Herein, we applied a machine learning algorithm to analyze data from a >20 year breast cancer (BC) registry elaborated in two Chilean health institutions (a public hospital and a private center) that includes  ...  ARTICLE INFO ABSTRACT In recent years, artificial intelligence (AI) and machine learning (a form of AI) have offered valuable tools for medicine by applying and training algorithms in order to make predictions  ...  Purpose As occurs in several countries, breast cancer (BC) is one of the leading causes of cancer related death among Chilean women [1] .  ... 
doi:10.26717/bjstr.2021.37.006037 fatcat:hzouptqm5jfhjgngpycs3j72ri

Applications of machine learning in cancer prediction and prognosis

Joseph A Cruz, David S Wishart
2007 Cancer Informatics  
As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction.  ...  In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction  ...  Conclusion In this review we have attempted to explain, compare and assess the performance of different machine learning that are being applied to cancer prediction and prognosis.  ... 
pmid:19458758 pmcid:PMC2675494 fatcat:ndhkyf6qdved3bq2ovahzduu7m

Using Machine Learning Algorithms for Breast Cancer Risk Prediction and Diagnosis

Hiba Asri, Hajar Mousannif, Hassan Al Moatassime, Thomas Noel
2016 Procedia Computer Science  
Breast Cancer (original) datasets is conducted.  ...  In this paper, a performance comparison between different machine learning algorithms: Support Vector Machine (SVM), Decision Tree (C4.5), Naive Bayes (NB) and k Nearest Neighbors (k-NN) on the Wisconsin  ...  Djebbari et al. 12 consider the effect of ensemble of machine learning techniques to predict the survival time in breast cancer.  ... 
doi:10.1016/j.procs.2016.04.224 fatcat:laffvmjou5hqvfk4vpnu6bqaqu

Breast cancer outcome prediction with tumour tissue images and machine learning

Riku Turkki, Dmitrii Byckhov, Mikael Lundin, Jorma Isola, Stig Nordling, Panu E. Kovanen, Clare Verrill, Karl von Smitten, Heikki Joensuu, Johan Lundin, Nina Linder
2019 Breast Cancer Research and Treatment  
factors in breast cancer.  ...  In univariate survival analysis, the DRS classification resulted in a hazard ratio of 2.10 (95% CI 1.33-3.32, p = 0.001) for breast cancer-specific survival.  ...  Conclusions We have demonstrated how machine learning analysis of tumour tissue images can be utilised for breast cancer patient prognostication.  ... 
doi:10.1007/s10549-019-05281-1 pmid:31119567 pmcid:PMC6647903 fatcat:3guvw4nfjnggtnuas3o4nj2ady

Applications of Machine Learning in Cancer Prediction and Prognosis

Joseph A. Cruz, David S. Wishart
2006 Cancer Informatics  
As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction.  ...  In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction  ...  Conclusion In this review we have attempted to explain, compare and assess the performance of different machine learning that are being applied to cancer prediction and prognosis.  ... 
doi:10.1177/117693510600200030 fatcat:w6rchn2oorbfnja5rh7uycvnm4

Early Detection of Breast Cancer Using Ensemble Machine Learning Algorithm [chapter]

Sainikhileaswar P S, Parthasarathy G
2020 Advances in Parallel Computing  
In order to improve breast cancer results and endurance, early recognition is significant. For detecting breast cancer growth early for the most part AI techniques are used.  ...  As showed by World Health Organization (WHO), Breast cancer growth is the most incessant disease among ladies, 627,000 ladies died due to breast cancer in the year 2018, which implies about 15 present  ...  Early detection is very essential in order to increase the breast cancer survival. Diagnosing breast cancer is done by tumour classification.  ... 
doi:10.3233/apc200204 fatcat:5r7w2kq6snaktfvvunkjatnvcm

Machine Learning With K-Means Dimensional Reduction for Predicting Survival Outcomes in Patients With Breast Cancer

Melissa Zhao, Yushi Tang, Hyunkyung Kim, Kohei Hasegawa
2018 Cancer Informatics  
Using machine learning methods to construct predictive models for 5-year survival in patients with breast cancer, we demonstrated discrimination ability across models with new insight into the stability  ...  and utility of dimensional reduction on genomic features in breast cancer survival prediction.  ...  Another study by Vanneschi et al 25 examined machine learning techniques for breast cancer survival using gene signatures alone.  ... 
doi:10.1177/1176935118810215 pmid:30455569 pmcid:PMC6238199 fatcat:ube3oac7j5e7pghwkz3qjwtry4

Analyzing Potential of SVM Based Classifiers for Intelligent and Less Invasive Breast Cancer Prognosis

Amna Ali, Umer Khan, Ali Tufail, Minkoo Kim
2010 2010 Second International Conference on Computer Engineering and Applications  
In this paper, we have targeted this strength of SVMs to analyze the potential of classification through feature vectors for predicting the survival chances of a breast cancer patient.  ...  SEER breast cancer data set , the most comprehensible source of information on cancer incidence in United States, is considered.  ...  potential of Support vector Machines for prediction of breast cancer survivability in particular, and breast cancer prognosis in general.  ... 
doi:10.1109/iccea.2010.212 fatcat:vzggubifsbfzfe3sbisweo3mhe

A Machine Learning Approach to Predict Stress Hormones and Inflammatory Markers Using Illness Perception and Quality of Life in Breast Cancer Patients

Irina Crumpei-Tanasă, Iulia Crumpei
2021 Current Oncology  
We use statistics and machine learning methods to analyze our data and find the best prediction model.  ...  We examine if illness perception and quality of life reports measured at baseline could predict the stress hormones and inflammatory markers in breast cancer survivors, one year later.  ...  Inflammation might be the frame explaining how illness perception can predict breast cancer survival outcomes.  ... 
doi:10.3390/curroncol28040275 pmid:34436041 pmcid:PMC8395480 fatcat:smydjue6qnfjnfhyhnrfycto4e

Tree-Based and Machine Learning Algorithm Analysis for Breast Cancer Classification

Arpit Bhardwaj, Harshit Bhardwaj, Aditi Sakalle, Ziya Uddin, Maneesha Sakalle, Wubshet Ibrahim, Abdul Rehman Javed
2022 Computational Intelligence and Neuroscience  
Breast cancer (BC) is the second leading cause of death in developed and developing nations, accounting for 8% of deaths after lung cancer.  ...  Gene mutation, constant pain, size fluctuations, colour (roughness), and breast skin texture are all characteristics of BC.  ...  [8] explore forecasting the survival time of breast cancer using machine learning. eir methodology exhibits improved precision compared to earlier outcomes using their breast cancer data. Liu et al  ... 
doi:10.1155/2022/6715406 pmid:35845866 pmcid:PMC9282979 fatcat:4wjs4cmuijbfvnemgx5uae2i74

Application of Machine Learning Models for Survival Prognosis in Breast Cancer Studies

Iliyan Mihaylov, Maria Nisheva, Dimitar Vassilev
2019 Information  
The application of machine learning models for accurate prediction of survival time in breast cancer on the basis of clinical data is the main objective of the presented study.  ...  Aside from data normalization and classification, the applied machine learning methods provide promising results in terms of accuracy of survival time prediction.  ...  Funding: The research presented in this paper has been supported by Project BG05M2OP001-1.001-0004 "Universities for Science, Informatics and Technologies in the e-Society (UNITe)" funded by Operational  ... 
doi:10.3390/info10030093 fatcat:yowotvaov5evzmv7szxz2s6iga

Predicting factors for survival of breast cancer patients using machine learning techniques

Mogana Darshini Ganggayah, Nur Aishah Taib, Yip Cheng Har, Pietro Lio, Sarinder Kaur Dhillon
2019 BMC Medical Informatics and Decision Making  
Conclusion: Interestingly the various machine learning algorithms used in this study yielded close accuracy hence these methods could be used as alternative predictive tools in the breast cancer survival  ...  As an alternative, this study used machine learning techniques to build models for detecting and visualising significant prognostic indicators of breast cancer survival rate.  ...  However, the (R version 3.5.1) source codes used to analyse breast cancer survival rate using machine learning techniques are deposited in GitHub (https://github.com/MoganaD/ Machine-Learning-on-Breast-Cancer-Survival-Prediction  ... 
doi:10.1186/s12911-019-0801-4 fatcat:5j36b753vffyzdswu65zqetrpu

Survival Outcome Prediction for Breast Cancer Patients

2020 International journal of recent technology and engineering  
We have used machine learning classification techniques to categorize benign and malignant tumors, in which the machine learns from past data and predicts the new input category.  ...  The second most causative disease is breast cancer happening in women and a significant explanation behind expanding death rate among women.  ...  Numerous researches are being led in this area by the use of different machine learning methods for various datasets on Breast cancer.  ... 
doi:10.35940/ijrte.a1592.059120 fatcat:jp6d22fv5vglvcpn7zth3kagui
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