"Unravelling Polypharmacy: Determining interaction patterns between medications using complex electronic health records for better patient care."
Lead Research Organisation:
Swansea University
Department Name: College of Science
Abstract
"The overall goal of this proposal is to develop a novel data-mining method to discover previously unknown patterns within the field of polypharmacy from patient records produced through EHRs in primary care settings. By focusing on novel methods for mining EHRs, a data-centric application can be tailored to the specific aspects of EHRs and polypharmacy. The project's objectives will focus on 4 topics:
1. How associations between multiple drugs evolve over time and differ between gender and age groups.
2. Which clusters of diseases are associated with certain polypharmacy prescriptions for patients.
3. How these patterns of intra-associations of multiple drugs are shaped from a young age.
4. The impact of the aforementioned results."
1. How associations between multiple drugs evolve over time and differ between gender and age groups.
2. Which clusters of diseases are associated with certain polypharmacy prescriptions for patients.
3. How these patterns of intra-associations of multiple drugs are shaped from a young age.
4. The impact of the aforementioned results."
Organisations
People |
ORCID iD |
Xianghua Xie (Primary Supervisor) | |
Gavin Tsang (Student) |
Publications
Tsang G
(2020)
Harnessing the Power of Machine Learning in Dementia Informatics Research: Issues, Opportunities, and Challenges
in IEEE Reviews in Biomedical Engineering
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
EP/N509553/1 | 30/09/2016 | 29/06/2022 | |||
1819112 | Studentship | EP/N509553/1 | 30/09/2016 | 29/09/2020 | Gavin Tsang |
Description | Effective stock market prediction based on machine learning algorithms involving Wavelet Decomposition, Autoencoders and LSTM Neural Networks. Risk factor identification of Hospitalisation in Dementia Sufferers using a combined feature selection, prediction Neural Network through the use of Entropy based weight regularisation. |
Exploitation Route | Future impacts within the field of finance pushing forward the established field of deep learning into a relatively untapped field. Continued identification and clinical analysis of risk factors brought forward for Hospitalisation in Dementia Sufferers to aid in more effective care and improve general outcomes. |
Sectors | Communities and Social Services/Policy Digital/Communication/Information Technologies (including Software) Financial Services and Management Consultancy Healthcare |