Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association

E Abels, L Pantanowitz, F Aeffner… - The Journal of …, 2019 - Wiley Online Library
In this white paper, experts from the Digital Pathology Association (DPA) define terminology
and concepts in the emerging field of computational pathology, with a focus on its …

[HTML][HTML] Named entity recognition and relation detection for biomedical information extraction

N Perera, M Dehmer, F Emmert-Streib - Frontiers in cell and …, 2020 - frontiersin.org
The number of scientific publications in the literature is steadily growing, containing our
knowledge in the biomedical, health, and clinical sciences. Since there is currently no …

[HTML][HTML] Natural language processing algorithms for mapping clinical text fragments onto ontology concepts: a systematic review and recommendations for future …

MG Kersloot, FJP van Putten, A Abu-Hanna… - Journal of biomedical …, 2020 - Springer
Background Free-text descriptions in electronic health records (EHRs) can be of interest for
clinical research and care optimization. However, free text cannot be readily interpreted by a …

Machine learning for detection and classification of oral potentially malignant disorders: A conceptual review

LL de Souza, FP Fonseca, ALD Araujo… - Journal of Oral …, 2023 - Wiley Online Library
Oral potentially malignant disorders represent precursor lesions that may undergo malignant
transformation to oral cancer. There are many known risk factors associated with the …

Dengue epidemics prediction: A survey of the state-of-the-art based on data science processes

P Siriyasatien, S Chadsuthi, K Jampachaisri… - IEEE …, 2018 - ieeexplore.ieee.org
Dengue infection is a mosquitoborne disease caused by dengue viruses, which are carried
by several species of mosquito of the genus Aedes, principally Ae. aegypti. Dengue …

[HTML][HTML] Improving broad-coverage medical entity linking with semantic type prediction and large-scale datasets

S Vashishth, D Newman-Griffis, R Joshi, R Dutt… - Journal of biomedical …, 2021 - Elsevier
Objectives Biomedical natural language processing tools are increasingly being applied for
broad-coverage information extraction—extracting medical information of all types in a …

[HTML][HTML] MedTAG: a portable and customizable annotation tool for biomedical documents

F Giachelle, O Irrera, G Silvello - BMC Medical Informatics and Decision …, 2021 - Springer
Abstract Background Semantic annotators and Natural Language Processing (NLP)
methods for Named Entity Recognition and Linking (NER+ L) require plenty of training and …

[HTML][HTML] Knowledge Graph Embeddings for ICU readmission prediction

RMS Carvalho, D Oliveira, C Pesquita - BMC Medical Informatics and …, 2023 - Springer
Abstract Background Intensive Care Unit (ICU) readmissions represent both a health risk for
patients, with increased mortality rates and overall health deterioration, and a financial …

[HTML][HTML] Data integration challenges for machine learning in precision medicine

M Martínez-García, E Hernández-Lemus - Frontiers in medicine, 2022 - frontiersin.org
A main goal of Precision Medicine is that of incorporating and integrating the vast corpora on
different databases about the molecular and environmental origins of disease, into analytic …

[PDF][PDF] Towards Semantic Integration for Explainable Artificial Intelligence in the Biomedical Domain.

C Pesquita - HEALTHINF, 2021 - pdfs.semanticscholar.org
Explainable artificial intelligence typically focuses on data-based explanations, lacking the
semantic context needed to produce human-centric explanations. This is especially relevant …