We present self-supervised iterative refinement learning (SIRL) as a pipeline to improve a type of macular optical coherence tomography (OCT) volumetric image classification algorithms. In this type of algorithms, first, two-dimensional (2D) image cl...
IEEE journal of biomedical and health informatics
Jun 14, 2019
In this paper, we propose a bi-modality medical image synthesis approach based on sequential generative adversarial network (GAN) and semi-supervised learning. Our approach consists of two generative modules that synthesize images of the two modaliti...
BACKGROUND: To improve the outcomes of biological pathway analysis, a better way of integrating pathway data is needed. Ontologies can be used to organize data from disparate sources, and we leverage the Pathway Ontology as a unifying ontology for or...
The availability of large-scale annotated image datasets and recent advances in supervised deep learning methods enable the end-to-end derivation of representative image features that can impact a variety of image analysis problems. Such supervised a...
The study shows the feasibility of predicting firms' expenditures in innovation, as reported in the Community Innovation Survey, applying a supervised machine-learning approach on a sample of Italian firms. Using an integrated dataset of administrati...
Neural networks : the official journal of the International Neural Network Society
Jun 7, 2019
As humans go through life sifting vast quantities of complex information, we extract knowledge from settings that are more ambiguous than our early homes and classrooms. Learning from experience in an individual's unique context generally improves ex...
The growing body of knowledge in biomedicine is too vast for human consumption. Hence there is a need for automated systems able to navigate and distill the emerging wealth of information. One fundamental task to that end is relation extraction, wher...
We propose a method to classify cardiac pathology based on a novel approach to extract image derived features to characterize the shape and motion of the heart. An original semi-supervised learning procedure, which makes efficient use of a large amou...
Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical images. Although supervised deep learning can perform accurate segmentation of pathological areas, it is limited by requiring a priori definitions of these regions...
Identifying unique patients across multiple care facilities or services is a major challenge in providing continuous care and undertaking health research. Identifying and linking patients without compromising privacy and security is an emerging issue...