A dataset and benchmark for hospital course summarization with adapted large language models.

Objective: Brief hospital course (BHC) summaries are clinical documents that summarize a patient's hospital stay. While large language models (LLMs) depict remarkable capabilities in automating real-world tasks, their capabilities for healthcare applications such as synthesizing BHCs from clinical notes have not been shown. We introduce a novel preprocessed dataset, the MIMIC-IV-BHC, encapsulating clinical note and BHC pairs to adapt LLMs for BHC synthesis.

Detection of neutralizing antibodies against arboviruses from liver homogenates.

Yellow fever virus (YFV) circulates in a sylvatic cycle between non-human primates (NHPs) and arboreal mosquitoes in Brazil. Passive monitoring of ill or deceased NHPs is a key component of the Brazilian yellow fever (YF) surveillance program. Samples from NHPs carcasses are usually suitable for molecular tests but not for serological assays.

Spatial and temporal modeling of the global burden of Cutaneous Leishmaniasis in Brazil: A 21-year ecological study.

Background: Cutaneous Leishmaniasis (CL) is a neglected tropical disease endemic in Brazil. Morbidity and disabilities caused by CL lesions require an analysis of a Global Burden of Disease (GBD), which would help discern the impact on the Brazilian population. Herein, we assess the burden of CL and its spatial and temporal patterns in Brazil between 2001 and 2021.

Advancing pharmacogenomics research: automated extraction of insights from PubMed using SpaCy NLP framework.

This paper presents a methodology for automatically extracting insights from PubMed articles using a Natural Language Processing (NLP) framework. Our approach, leveraging advanced NLP techniques and Named Entity Recognition (NER), is crucial for advancing pharmacogenomics and other scientific fields that benefit from streamlined access to literature through automated services like RESTful APIs.Building a new NLP model presents several challenges.