AIMC Topic: Biological Ontologies

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Predicting activities of daily living for cancer patients using an ontology-guided machine learning methodology.

Journal of biomedical semantics
BACKGROUND: Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to the SEER-MHOS dataset to dis...

Design of an extensive information representation scheme for clinical narratives.

Journal of biomedical semantics
BACKGROUND: Knowledge representation frameworks are essential to the understanding of complex biomedical processes, and to the analysis of biomedical texts that describe them. Combined with natural language processing (NLP), they have the potential t...

Ontology-based specification, identification and analysis of perioperative risks.

Journal of biomedical semantics
BACKGROUND: Medical personnel in hospitals often works under great physical and mental strain. In medical decision-making, errors can never be completely ruled out. Several studies have shown that between 50 and 60% of adverse events could have been ...

Semantic Modeling for Exposomics with Exploratory Evaluation in Clinical Context.

Journal of healthcare engineering
Exposome is a critical dimension in the precision medicine paradigm. Effective representation of exposomics knowledge is instrumental to melding nongenetic factors into data analytics for clinical research. There is still limited work in (1) modeling...

Discovering associations between adverse drug events using pattern structures and ontologies.

Journal of biomedical semantics
BACKGROUND: Patient data, such as electronic health records or adverse event reporting systems, constitute an essential resource for studying Adverse Drug Events (ADEs). We explore an original approach to identify frequently associated ADEs in subgro...

Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies.

Artificial intelligence in medicine
OBJECTIVE: Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an on...

An ontology-driven tool for structured data acquisition using Web forms.

Journal of biomedical semantics
BACKGROUND: Structured data acquisition is a common task that is widely performed in biomedicine. However, current solutions for this task are far from providing a means to structure data in such a way that it can be automatically employed in decisio...

Towards a more molecular taxonomy of disease.

Journal of biomedical semantics
BACKGROUND: Disease taxonomies have been designed for many applications, but they tend not to fully incorporate the growing amount of molecular-level knowledge of disease processes, inhibiting research efforts. Understanding the degree to which we ca...

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals.

Journal of medical Internet research
BACKGROUND: Social networking services (SNSs) contain abundant information about the feelings, thoughts, interests, and patterns of behavior of adolescents that can be obtained by analyzing SNS postings. An ontology that expresses the shared concepts...

Lightweight predicate extraction for patient-level cancer information and ontology development.

BMC medical informatics and decision making
BACKGROUND: Knowledge engineering for ontological knowledgebases is resource and time intensive. To alleviate these issues, especially for novices, automated tools from the natural language domain can assist in the development process of ontologies. ...