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 …

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 …

Knowledge graph enrichment from clinical narratives using NLP, NER, and biomedical ontologies for healthcare applications

A Thukral, S Dhiman, R Meher, P Bedi - International Journal of …, 2023 - Springer
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 …

Biomedical data, computational methods and tools for evaluating disease–disease associations

J Xiang, J Zhang, Y Zhao, FX Wu… - Briefings in …, 2022 - academic.oup.com
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 …

Diseasomics: Actionable machine interpretable disease knowledge at the point-of-care

AK Talukder, L Schriml, A Ghosh, R Biswas… - PLOS Digital …, 2022 - journals.plos.org
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 …

Knowledge graphs for the life sciences: Recent developments, challenges and opportunities

J Chen, H Dong, J Hastings, E Jiménez-Ruiz… - arXiv preprint arXiv …, 2023 - arxiv.org
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 …

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 …

[HTML][HTML] A corpus-driven standardization framework for encoding clinical problems with HL7 FHIR

KJ Peterson, G Jiang, H Liu - Journal of biomedical informatics, 2020 - Elsevier
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 …

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 …

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 …