AIMC Topic: Natural Language Processing

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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.

Explainable hybrid word representations for sentiment analysis of financial news.

Neural networks : the official journal of the International Neural Network Society
Due to the increasing interest of people in the stock and financial market, the sentiment analysis of news and texts related to the sector is of utmost importance. This helps the potential investors in deciding what company to invest in and what are ...

Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging.

AJR. American journal of roentgenology
Reported rates of recommendations for additional imaging (RAIs) in radiology reports are low. Bidirectional encoder representations from transformers (BERT), a deep learning model pretrained to understand language context and ambiguity, has potentia...

Leveraging Knowledge Graphs and Natural Language Processing for Automated Web Resource Labeling and Knowledge Mobilization in Neurodevelopmental Disorders: Development and Usability Study.

Journal of medical Internet research
BACKGROUND: Patients and families need to be provided with trusted information more than ever with the abundance of online information. Several organizations aim to build databases that can be searched based on the needs of target groups. One such gr...

Piloting an automated clinical trial eligibility surveillance and provider alert system based on artificial intelligence and standard data models.

BMC medical research methodology
BACKGROUND: To advance new therapies into clinical care, clinical trials must recruit enough participants. Yet, many trials fail to do so, leading to delays, early trial termination, and wasted resources. Under-enrolling trials make it impossible to ...

Deep learning-based detection of patients with bone metastasis from Japanese radiology reports.

Japanese journal of radiology
PURPOSE: Deep learning (DL) is a state-of-the-art technique for developing artificial intelligence in various domains and it improves the performance of natural language processing (NLP). Therefore, we aimed to develop a DL-based NLP model that class...

The use of artificial intelligence to detect students' sentiments and emotions in gross anatomy reflections.

Anatomical sciences education
Students' reflective writings in gross anatomy provide a rich source of complex emotions experienced by learners. However, qualitative approaches to evaluating student writings are resource heavy and timely. To overcome this, natural language process...