11 research outputs found
Multimorbidity Content-Based Medical Image Retrieval Using Proxies
Content-based medical image retrieval is an important diagnostic tool that
improves the explainability of computer-aided diagnosis systems and provides
decision making support to healthcare professionals. Medical imaging data, such
as radiology images, are often multimorbidity; a single sample may have more
than one pathology present. As such, image retrieval systems for the medical
domain must be designed for the multi-label scenario. In this paper, we propose
a novel multi-label metric learning method that can be used for both
classification and content-based image retrieval. In this way, our model is
able to support diagnosis by predicting the presence of diseases and provide
evidence for these predictions by returning samples with similar pathological
content to the user. In practice, the retrieved images may also be accompanied
by pathology reports, further assisting in the diagnostic process. Our method
leverages proxy feature vectors, enabling the efficient learning of a robust
feature space in which the distance between feature vectors can be used as a
measure of the similarity of those samples. Unlike existing proxy-based
methods, training samples are able to assign to multiple proxies that span
multiple class labels. This multi-label proxy assignment results in a feature
space that encodes the complex relationships between diseases present in
medical imaging data. Our method outperforms state-of-the-art image retrieval
systems and a set of baseline approaches. We demonstrate the efficacy of our
approach to both classification and content-based image retrieval on two
multimorbidity radiology datasets
Informatics for Health 2017 : advancing both science and practice
Conference report, The Informatics for Health congress, 24-26 April 2017, in Manchester, UK.Introduction : The Informatics for Health congress, 24-26 April 2017, in Manchester, UK, brought together the Medical Informatics Europe (MIE) conference and the Farr Institute International Conference. This special issue of the Journal of Innovation in Health Informatics contains 113 presentation abstracts and 149 poster abstracts from the congress. Discussion : The twin programmes of “Big Data” and “Digital Health” are not always joined up by coherent policy and investment priorities. Substantial global investment in health IT and data science has led to sound progress but highly variable outcomes. Society needs an approach that brings together the science and the practice of health informatics. The goal is multi-level Learning Health Systems that consume and intelligently act upon both patient data and organizational intervention outcomes. Conclusions : Informatics for Health demonstrated the art of the possible, seen in the breadth and depth of our contributions. We call upon policy makers, research funders and programme leaders to learn from this joined-up approach.Publisher PDFPeer reviewe
Pacific Symposium on Biocomputing 2023
The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field