AIMC Topic: Natural Language Processing

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Advancing plant biology through deep learning-powered natural language processing.

Plant cell reports
The application of deep learning methods, specifically the utilization of Large Language Models (LLMs), in the field of plant biology holds significant promise for generating novel knowledge on plant cell systems. The LLM framework exhibits exception...

Overview of computational methods in taphonomy based on the combination of bibliometric analysis and natural language.

Anais da Academia Brasileira de Ciencias
Artificial intelligence tools are new in taphonomy and are growing fast. They are being used mainly to investigate bone surface marks. In order to investigate this subject, a bibliometric study was made to understand the growing rate of this intersec...

Assessing dimensions of thought disorder with large language models: The tradeoff of accuracy and consistency.

Psychiatry research
Natural Language Processing (NLP) methods have shown promise for the assessment of formal thought disorder, a hallmark feature of schizophrenia in which disturbances to the structure, organization, or coherence of thought can manifest as disordered o...

A pre-trained language model for emergency department intervention prediction using routine physiological data and clinical narratives.

International journal of medical informatics
INTRODUCTION: The urgency and complexity of emergency room (ER) settings require precise and swift decision-making processes for patient care. Ensuring the timely execution of critical examinations and interventions is vital for reducing diagnostic e...

MIGP: Metapath Integrated Graph Prompt Neural Network.

Neural networks : the official journal of the International Neural Network Society
Graph neural networks (GNNs) leveraging metapaths have garnered extensive utilization. Nevertheless, the escalating parameters and data corpus within graph pre-training models incur mounting training costs. Consequently, GNN models encounter hurdles ...

Botulinum Toxin Type A (BoNT-A) Use for Post-Stroke Spasticity: A Multicenter Study Using Natural Language Processing and Machine Learning.

Toxins
We conducted a multicenter and retrospective study to describe the use of botulinum toxin type A (BoNT-A) to treat post-stroke spasticity (PSS). Data were extracted from free-text in electronic health records (EHRs) in five Spanish hospitals. We incl...

BrainNPT: Pre-Training Transformer Networks for Brain Network Classification.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Deep learning methods have advanced quickly in brain imaging analysis over the past few years, but they are usually restricted by the limited labeled data. Pre-trained model on unlabeled data has presented promising improvement in feature learning in...

Artificial Intelligence: A Help or Hindrance to Scientific Writing?

Annals of surgery
We have assessed the chatbot Generative Pretrained Transformer, a type of artificial intelligence software designed to simulate conversations with human users, in an experiment designed to test its relevance to scientific writing. chatbot Generative ...

Enhancing Postmarketing Surveillance of Medical Products With Large Language Models.

JAMA network open
IMPORTANCE: The Sentinel System is a key component of the US Food and Drug Administration (FDA) postmarketing safety surveillance commitment and uses clinical health care data to conduct analyses to inform drug labeling and safety communications, FDA...

Classification of Patients' Judgments of Their Physicians in Web-Based Written Reviews Using Natural Language Processing: Algorithm Development and Validation.

Journal of medical Internet research
BACKGROUND: Patients increasingly rely on web-based physician reviews to choose a physician and share their experiences. However, the unstructured text of these written reviews presents a challenge for researchers seeking to make inferences about pat...