AI Medical Compendium Topic

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Lit-OTAR framework for extracting biological evidences from literature.

Bioinformatics (Oxford, England)
SUMMARY: The lit-OTAR framework, developed through a collaboration between Europe PMC and Open Targets, leverages deep learning to revolutionize drug discovery by extracting evidence from scientific literature for drug target identification and valid...

Assessing citation integrity in biomedical publications: corpus annotation and NLP models.

Bioinformatics (Oxford, England)
MOTIVATION: Citations have a fundamental role in scholarly communication and assessment. Citation accuracy and transparency is crucial for the integrity of scientific evidence. In this work, we focus on quotation errors, errors in citation content th...

Applying BERT and ChatGPT for Sentiment Analysis of Lyme Disease in Scientific Literature.

Methods in molecular biology (Clifton, N.J.)
This chapter presents a practical guide for conducting sentiment analysis using Natural Language Processing (NLP) techniques in the domain of tick-borne disease text. The aim is to demonstrate the process of how the presence of bias in the discourse ...

Research progress of the artificial intelligence application in wastewater treatment during 2012-2022: a bibliometric analysis.

Water science and technology : a journal of the International Association on Water Pollution Research
This study identified literatures from the Web of Science Core Collection on the application of artificial intelligence in wastewater treatment from 2011 to 2022, through bibliometrics, to summarize achievements and capture the scientific and technol...

Predicting cross-tissue hormone-gene relations using balanced word embeddings.

Bioinformatics (Oxford, England)
MOTIVATION: Inter-organ/inter-tissue communication is central to multi-cellular organisms including humans, and mapping inter-tissue interactions can advance system-level whole-body modeling efforts. Large volumes of biomedical literature have foster...

Avoiding C-hacking when evaluating survival distribution predictions with discrimination measures.

Bioinformatics (Oxford, England)
MOTIVATION: In this article, we consider how to evaluate survival distribution predictions with measures of discrimination. This is non-trivial as discrimination measures are the most commonly used in survival analysis and yet there is no clear metho...