AIMC Topic: Natural Language Processing

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Negation and speculation processing: A study on cue-scope labelling and assertion classification in Spanish clinical text.

Artificial intelligence in medicine
Natural Language Processing (NLP) based on new deep learning technology is contributing to the emergence of powerful solutions that help healthcare providers and researchers discover valuable patterns within insurmountable volumes of health records a...

Artificial Intelligence for Quantitative Modeling in Drug Discovery and Development: An Innovation and Quality Consortium Perspective on Use Cases and Best Practices.

Clinical pharmacology and therapeutics
Recent breakthroughs in artificial intelligence (AI) and machine learning (ML) have ushered in a new era of possibilities across various scientific domains. One area where these advancements hold significant promise is model-informed drug discovery a...

Natural language processing for mental health interventions: a systematic review and research framework.

Translational psychiatry
Neuropsychiatric disorders pose a high societal cost, but their treatment is hindered by lack of objective outcomes and fidelity metrics. AI technologies and specifically Natural Language Processing (NLP) have emerged as tools to study mental health ...

Revealing Academic Evolution and Frontier Pattern in the Field of Uveitis Using Bibliometric Analysis, Natural Language Processing, and Machine Learning.

Ocular immunology and inflammation
PURPOSE: Numerous uveitis articles were published in this century, underneath which hides valuable intelligence. We aimed to characterize the evolution and patterns in this field.

Effects of MRI scanner manufacturers in classification tasks with deep learning models.

Scientific reports
Deep learning has become a leading subset of machine learning and has been successfully employed in diverse areas, ranging from natural language processing to medical image analysis. In medical imaging, researchers have progressively turned towards m...

Leveraging Summary Guidance on Medical Report Summarization.

IEEE journal of biomedical and health informatics
This study presents three deidentified large medical text datasets, named DISCHARGE, ECHO and RADIOLOGY, which contain 50 K, 16 K and 378 K pairs of report and summary that are derived from MIMIC-III, respectively. We implement convincing baselines o...

A Review of Recurrent Neural Network-Based Methods in Computational Physiology.

IEEE transactions on neural networks and learning systems
Artificial intelligence and machine learning techniques have progressed dramatically and become powerful tools required to solve complicated tasks, such as computer vision, speech recognition, and natural language processing. Since these techniques h...

STTRE: A Spatio-Temporal Transformer with Relative Embeddings for multivariate time series forecasting.

Neural networks : the official journal of the International Neural Network Society
The prevalence of multivariate time series data across several disciplines fosters a demand and, subsequently, significant growth in the research and advancement of multivariate time series analysis. Drawing inspiration from a popular natural languag...

Surgery's Rosetta Stone: Natural language processing to predict discharge and readmission after general surgery.

Surgery
BACKGROUND: This study aimed to examine the accuracy with which multiple natural language processing artificial intelligence models could predict discharge and readmissions after general surgery.