A5077961086- Biomedical Text Mining and Ontologies
- Topic Modeling
- Genomics and Rare Diseases
- Laser-Plasma Interactions and Diagnostics
- Bioinformatics and Genomic Networks
- Magnetic confinement fusion research
- Machine Learning in Healthcare
- Fusion materials and technologies
University of Birmingham
2021-2022
University Hospitals Birmingham NHS Foundation Trust
2021
Ontology-based phenotype profiles have been utilised for the purpose of differential diagnosis rare genetic diseases, and decision support in specific disease domains. Particularly, semantic similarity facilitates diagnostic hypothesis generation through comparison with profiles. However, approach has not applied common or generalised clinical diagnostics from uncurated text-derived phenotypes. In this work, we describe development an deriving patient narrative text, apply to text associated...
Abstract Ontology-based phenotype profiles have been utilised for the purpose of differential diagnosis rare genetic diseases, and decision support in specific disease domains. Particularly, semantic similarity facilitates diagnostic hypothesis generation through comparison with profiles. However, approach has not applied common or generalised clinical diagnostics from uncurated text-derived phenotypes. In this work, we describe development an deriving patient narrative text, apply to text...
Abstract Background Semantic similarity is a valuable tool for analysis in biomedicine. When applied to phenotype profiles derived from clinical text, they have the capacity enable and enhance ‘patient-like me’ analyses, automated coding, differential diagnosis, outcome prediction. While large body of work exists exploring use semantic multiple tasks, including protein interaction prediction, rare disease there less comparison patient tasks. Moreover, are no experimental explorations optimal...
Abstract Semantic similarity is a valuable tool for analysis in biomedicine. When applied to phenotype profiles derived from clinical text, they have the capacity enable and enhance ‘patient-like me’ analyses, automated coding, differential diagnosis, outcome prediction, by leveraging wealth of background knowledge provided biomedical ontologies. While large body work exists exploring use semantic multiple tasks, including protein interaction rare disease there less comparison patient tasks....