AIMC Topic: Information Storage and Retrieval

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PIPER: A logic-driven deep contrastive optimization pipeline for event temporal reasoning.

Neural networks : the official journal of the International Neural Network Society
Event temporal relation extraction is an important task for information extraction. The existing methods usually rely on feature engineering and require post-process to achieve optimization, though inconsistent optimization may occur in the post-proc...

Contextualized medication information extraction using Transformer-based deep learning architectures.

Journal of biomedical informatics
OBJECTIVE: To develop a natural language processing (NLP) system to extract medications and contextual information that help understand drug changes. This project is part of the 2022 n2c2 challenge.

Review of Natural Language Processing in Pharmacology.

Pharmacological reviews
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, and use it in various applications. This area has rapidly developed in the...

Natural Language Processing in Electronic Health Records in relation to healthcare decision-making: A systematic review.

Computers in biology and medicine
BACKGROUND: Natural Language Processing (NLP) is widely used to extract clinical insights from Electronic Health Records (EHRs). However, the lack of annotated data, automated tools, and other challenges hinder the full utilisation of NLP for EHRs. V...

DR.BENCH: Diagnostic Reasoning Benchmark for Clinical Natural Language Processing.

Journal of biomedical informatics
The meaningful use of electronic health records (EHR) continues to progress in the digital era with clinical decision support systems augmented by artificial intelligence. A priority in improving provider experience is to overcome information overloa...

Negation detection in Dutch clinical texts: an evaluation of rule-based and machine learning methods.

BMC bioinformatics
When developing models for clinical information retrieval and decision support systems, the discrete outcomes required for training are often missing. These labels need to be extracted from free text in electronic health records. For this extraction ...

A study on pharmaceutical text relationship extraction based on heterogeneous graph neural networks.

Mathematical biosciences and engineering : MBE
Effective information extraction of pharmaceutical texts is of great significance for clinical research. The ancient Chinese medicine text has streamlined sentences and complex semantic relationships, and the textual relationships may exist between h...

Entity relationship extraction from Chinese electronic medical records based on feature augmentation and cascade binary tagging framework.

Mathematical biosciences and engineering : MBE
Extracting entity relations from unstructured Chinese electronic medical records is an important task in medical information extraction. However, Chinese electronic medical records mostly have document-level volumes, and existing models are either un...

A systematic review on the state-of-the-art strategies for protein representation.

Computers in biology and medicine
The study of drug-target protein interaction is a key step in drug research. In recent years, machine learning techniques have become attractive for research, including drug research, due to their automated nature, predictive power, and expected effi...

Machine understanding surgical actions from intervention procedure textbooks.

Computers in biology and medicine
The automatic extraction of procedural surgical knowledge from surgery manuals, academic papers or other high-quality textual resources, is of the utmost importance to develop knowledge-based clinical decision support systems, to automatically execut...