Supervised deep learning embeddings for the prediction of cervical cancer diagnosis
Open Access
- 14 May 2018
- journal article
- research article
- Published by PeerJ in PeerJ Computer Science
- Vol. 4, e154
- https://doi.org/10.7717/peerj-cs.154
Abstract
Cervical cancer remains a significant cause of mortality all around the world, even if it can be prevented and cured by removing affected tissues in early stages. Providing universal and efficient access to cervical screening programs is a challenge that requires identifying vulnerable individuals in the population, among other steps. In this work, we present a computationally automated strategy for predicting the outcome of the patient biopsy, given risk patterns from individual medical records. We propose a machine learning technique that allows a joint and fully supervised optimization of dimensionality reduction and classification models. We also build a model able to highlight relevant properties in the low dimensional space, to ease the classification of patients. We instantiated the proposed approach with deep learning architectures, and achieved accurate prediction results (top area under the curve AUC = 0.6875) which outperform previously developed methods, such as denoising autoencoders. Additionally, we explored some clinical findings from the embedding spaces, and we validated them through the medical literature, making them reliable for physicians and biomedical researchers.Keywords
Funding Information
- NanoSTIMA: Macro-to-Nano Human Sensing: Towards Integrated Multimodal Health Monitoring and Analytics (NORTE-01-0145-FEDER-000016)
- North Portugal Regional Operational Programme (NORTE 2020)
- PORTUGAL 2020 Partnership Agreement
- European Regional Development Fund (ERDF)
- Fundação para a Ciência e a Tecnologia (FCT) (SFRH/BD/93012/2013)
This publication has 31 references indexed in Scilit:
- Current Recommendations for Cervical Cancer Screening: Do They Render the Annual Pelvic Examination Obsolete?Medical Principles and Practice, 2013
- A Review of Automated Techniques for Cervical Cell Image Analysis and ClassificationPublished by Springer Science and Business Media LLC ,2012
- Early age at first sexual intercourse and early pregnancy are risk factors for cervical cancer in developing countriesBritish Journal of Cancer, 2009
- K-nearest neighborScholarpedia, 2009
- Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice Disorder DetectionBioMedical Engineering OnLine, 2007
- Computational analysis of gene-gene interactions using multifactor dimensionality reductionExpert Review of Molecular Diagnostics, 2004
- SisPorto 2.0: A Program for Automated Analysis of CardiotocogramsThe Journal of Maternal-Fetal & Neonatal Medicine, 2000
- Comparing support vector machines with Gaussian kernels to radial basis function classifiersIEEE Transactions on Signal Processing, 1997
- Optimal discriminant plane for a small number of samples and design method of classifier on the planePattern Recognition, 1991
- Induction of decision treesMachine Learning, 1986