Computational prediction of diagnosis and feature selection on mesothelioma patient health records
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Computational prediction of diagnosis and feature selection on mesothelioma patient health records
Authors
Keywords
Mesothelioma, Decision trees, Pleurae, Machine learning, Platelets, Neural networks, Decision tree learning, Body fluids
Journal
PLoS One
Volume 14, Issue 1, Pages e0208737
Publisher
Public Library of Science (PLoS)
Online
2019-01-11
DOI
10.1371/journal.pone.0208737
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Classification and interaction in random forests
- (2018) Danielle Denisko et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Classifying and segmenting microscopy images with deep multiple instance learning
- (2016) Oren Z. Kraus et al. BIOINFORMATICS
- Predicting the Future — Big Data, Machine Learning, and Clinical Medicine
- (2016) Ziad Obermeyer et al. NEW ENGLAND JOURNAL OF MEDICINE
- Computational algorithms to predict Gene Ontology annotations
- (2015) Pietro Pinoli et al. BMC BIOINFORMATICS
- Software Suite for Gene and Protein Annotation Prediction and Similarity Search
- (2015) Davide Chicco et al. IEEE-ACM Transactions on Computational Biology and Bioinformatics
- Classification of lung cancer using ensemble-based feature selection and machine learning methods
- (2015) Zhihua Cai et al. Molecular BioSystems
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
- (2015) Babak Alipanahi et al. NATURE BIOTECHNOLOGY
- Machine learning applications in cancer prognosis and prediction
- (2015) Konstantina Kourou et al. Computational and Structural Biotechnology Journal
- A Review of Ensemble Learning Based Feature Selection
- (2014) Donghai Guan et al. IETE TECHNICAL REVIEW
- Validation of Prognostic Factors in Malignant Pleural Mesothelioma: A Retrospective Analysis of Data from Patients Seeking Compensation from the New South Wales Dust Diseases Board
- (2012) Steven C. Kao et al. Clinical Lung Cancer
- Probabilistic neural network for breast cancer classification
- (2012) Ahmad Taher Azar et al. NEURAL COMPUTING & APPLICATIONS
- Predicting disease risks from highly imbalanced data using random forest
- (2011) Mohammed Khalilia et al. BMC Medical Informatics and Decision Making
- Global mesothelioma deaths reported to the World Health Organization between 1994 and 2008
- (2011) Vanya Delgermaa et al. BULLETIN OF THE WORLD HEALTH ORGANIZATION
- An approach based on probabilistic neural network for diagnosis of Mesothelioma’s disease
- (2011) Orhan Er et al. COMPUTERS & ELECTRICAL ENGINEERING
- Permutation importance: a corrected feature importance measure
- (2010) André Altmann et al. BIOINFORMATICS
- Cluster-based under-sampling approaches for imbalanced data distributions
- (2008) Show-Jane Yen et al. EXPERT SYSTEMS WITH APPLICATIONS
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started