Representation learning for mammography mass lesion classification with convolutional neural networks
Background and objective The automatic classification of breast imaging lesions is currently
an unsolved problem. This paper describes an innovative representation learning …
an unsolved problem. This paper describes an innovative representation learning …
[PDF][PDF] BCDR: a breast cancer digital repository
This paper outlines the first Portuguese “Breast Cancer Digital Repository”(BCDR-FMR), a
comprehensive annotated repository including digital content (digitized film mammography …
comprehensive annotated repository including digital content (digitized film mammography …
A decision support system for classification of normal and medical renal disease using ultrasound images: a decision support system for medical renal diseases
Early detection of medical renal disease is important as the same may lead to chronic kidney
disease which is an irreversible stage. The present work proposes an efficient decision …
disease which is an irreversible stage. The present work proposes an efficient decision …
[PDF][PDF] Encog: library of interchangeable machine learning models for Java and C#.
J Heaton - J. Mach. Learn. Res., 2015 - jmlr.org
This paper introduces the Encog library for Java and C#, a scalable, adaptable,
multiplatform machine learning framework that was first released in 2008. Encog allows a …
multiplatform machine learning framework that was first released in 2008. Encog allows a …
Hybrid disease diagnosis using multiobjective optimization with evolutionary parameter optimization
With the widespread adoption of e‐Healthcare and telemedicine applications, accurate,
intelligent disease diagnosis systems have been profoundly coveted. In recent years …
intelligent disease diagnosis systems have been profoundly coveted. In recent years …
[PDF][PDF] Counting and exploring sizes of Markov equivalence classes of directed acyclic graphs
When learning a directed acyclic graph (DAG) model via observational data, one generally
cannot identify the underlying DAG, but can potentially obtain a Markov equivalence class …
cannot identify the underlying DAG, but can potentially obtain a Markov equivalence class …
Benchmarking datasets for breast cancer computer-aided diagnosis (CADx)
Designing reliable computer-aided diagnosis (CADx) systems based on data extracted from
breast images and patient data to provide a second opinion to radiologists is still a …
breast images and patient data to provide a second opinion to radiologists is still a …
Search for β2 Adrenergic Receptor Ligands by Virtual Screening via Grid Computing and Investigation of Binding Modes by Docking and Molecular Dynamics …
We designed a program called MolGridCal that can be used to screen small molecule
database in grid computing on basis of JPPF grid environment. Based on MolGridCal …
database in grid computing on basis of JPPF grid environment. Based on MolGridCal …
Development of a strategy to predict and detect falls using wearable sensors
Falls are a prevalent problem in actual society. Some falls result in injuries and the cost
associated with their treatment is high. This is a complex problem that requires several steps …
associated with their treatment is high. This is a complex problem that requires several steps …
Using data mining techniques to support breast cancer diagnosis
J Diz, G Marreiros, A Freitas - New Contributions in Information Systems …, 2015 - Springer
More than ever, in breast cancer research, many computer aided diagnostic systems have
been developed in order to reduce false-positives diagnosis. In this work, we present a data …
been developed in order to reduce false-positives diagnosis. In this work, we present a data …