AIMC Topic: Natural Language Processing

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CLDTLog: System Log Anomaly Detection Method Based on Contrastive Learning and Dual Objective Tasks.

Sensors (Basel, Switzerland)
System logs are a crucial component of system maintainability, as they record the status of the system and essential events for troubleshooting and maintenance when necessary. Therefore, anomaly detection of system logs is crucial. Recent research ha...

A novel gluten knowledge base of potential biomedical and health-related interactions extracted from the literature: Using machine learning and graph analysis methodologies to reconstruct the bibliome.

Journal of biomedical informatics
BACKGROUND: In return for their nutritional properties and broad availability, cereal crops have been associated with different alimentary disorders and symptoms, with the majority of the responsibility being attributed to gluten. Therefore, the rese...

Patient Dietary Supplements Use: Do Results from Natural Language Processing of Clinical Notes Agree with Survey Data?

Medical sciences (Basel, Switzerland)
There is widespread use of dietary supplements, some prescribed but many taken without a physician's guidance. There are many potential interactions between supplements and both over-the-counter and prescription medications in ways that are unknown t...

Use and Design of Chatbots for the Circular Economy.

Sensors (Basel, Switzerland)
The fact that advanced technologies and their economic applications have generated increasing resource costs justifies the transition from a linear approach to a circular one in order to control these costs. From this perspective, this study presents...

FooDis: A food-disease relation mining pipeline.

Artificial intelligence in medicine
Nowadays, it is really important and crucial to follow the new biomedical knowledge that is presented in scientific literature. To this end, Information Extraction pipelines can help to automatically extract meaningful relations from textual data tha...

Medication event extraction in clinical notes: Contribution of the WisPerMed team to the n2c2 2022 challenge.

Journal of biomedical informatics
In this work, we describe the findings of the 'WisPerMed' team from their participation in Track 1 (Contextualized Medication Event Extraction) of the n2c2 2022 challenge. We tackle two tasks: (i) medication extraction, which involves extracting all ...

KEBLM: Knowledge-Enhanced Biomedical Language Models.

Journal of biomedical informatics
Pretrained language models (PLMs) have demonstrated strong performance on many natural language processing (NLP) tasks. Despite their great success, these PLMs are typically pretrained only on unstructured free texts without leveraging existing struc...

Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

JMIR public health and surveillance
BACKGROUND: Fatal drug overdose surveillance informs prevention but is often delayed because of autopsy report processing and death certificate coding. Autopsy reports contain narrative text describing scene evidence and medical history (similar to p...

On the fractal patterns of language structures.

PloS one
Natural Language Processing (NLP) makes use of Artificial Intelligence algorithms to extract meaningful information from unstructured texts, i.e., content that lacks metadata and cannot easily be indexed or mapped onto standard database fields. It ha...

A Joint Extraction System Based on Conditional Layer Normalization for Health Monitoring.

Sensors (Basel, Switzerland)
Natural language processing (NLP) technology has played a pivotal role in health monitoring as an important artificial intelligence method. As a key technology in NLP, relation triplet extraction is closely related to the performance of health monito...