Knowledge-based biomedical data science
TJ Callahan, IJ Tripodi… - Annual review of …, 2020 - annualreviews.org
Knowledge-based biomedical data science involves the design and implementation of
computer systems that act as if they knew about biomedicine. Such systems depend on …
computer systems that act as if they knew about biomedicine. Such systems depend on …
Review of natural language processing in pharmacology
D Trajanov, V Trajkovski, M Dimitrieva, J Dobreva… - Pharmacological …, 2023 - Elsevier
Natural language processing (NLP) is an area of artificial intelligence that applies
information technologies to process the human language, understand it to a certain degree …
information technologies to process the human language, understand it to a certain degree …
Knowledge graph enrichment from clinical narratives using NLP, NER, and biomedical ontologies for healthcare applications
Electronic health records (EHR) contain patients' health information in varied formats such
as clinical reports written in natural language, X-rays, MRI, case/discharge-summary, etc …
as clinical reports written in natural language, X-rays, MRI, case/discharge-summary, etc …
Biomedical data, computational methods and tools for evaluating disease–disease associations
In recent decades, exploring potential relationships between diseases has been an active
research field. With the rapid accumulation of disease-related biomedical data, a lot of …
research field. With the rapid accumulation of disease-related biomedical data, a lot of …
Diseasomics: Actionable machine interpretable disease knowledge at the point-of-care
Physicians establish diagnosis by assessing a patient's signs, symptoms, age, sex,
laboratory test findings and the disease history. All this must be done in limited time and …
laboratory test findings and the disease history. All this must be done in limited time and …
Knowledge graphs for the life sciences: Recent developments, challenges and opportunities
The term life sciences refers to the disciplines that study living organisms and life processes,
and include chemistry, biology, medicine, and a range of other related disciplines. Research …
and include chemistry, biology, medicine, and a range of other related disciplines. Research …
DISNET: a framework for extracting phenotypic disease information from public sources
G Lagunes-García, A Rodríguez-González… - PeerJ, 2020 - peerj.com
Background Within the global endeavour of improving population health, one major
challenge is the identification and integration of medical knowledge spread through several …
challenge is the identification and integration of medical knowledge spread through several …
[HTML][HTML] A corpus-driven standardization framework for encoding clinical problems with HL7 FHIR
Free-text problem descriptions are brief explanations of patient diagnoses and issues,
commonly found in problem lists and other prominent areas of the medical record. These …
commonly found in problem lists and other prominent areas of the medical record. These …
From language models to large-scale food and biomedical knowledge graphs
G Cenikj, L Strojnik, R Angelski, N Ogrinc… - Scientific reports, 2023 - nature.com
Abstract Knowledge about the interactions between dietary and biomedical factors is
scattered throughout uncountable research articles in an unstructured form (eg, text, images …
scattered throughout uncountable research articles in an unstructured form (eg, text, images …
Identifying symptom etiologies using syntactic patterns and large language models
H Taub-Tabib, Y Shamay, M Shlain, M Pinhasov… - Scientific Reports, 2024 - nature.com
Differential diagnosis is a crucial aspect of medical practice, as it guides clinicians to
accurate diagnoses and effective treatment plans. Traditional resources, such as medical …
accurate diagnoses and effective treatment plans. Traditional resources, such as medical …