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Fractals and artificial intelligence to decrypt ideography and understand the evolution of language.

The Behavioral and brain sciences
Self-sufficient ideographies are rare because they are stifled by the issue of standardization. Similar issues arise with abstract art or drawings created by young children or great apes. We propose that mathematical indices and artificial intelligen...

Tell me your position: Distantly supervised biomedical entity relation extraction using entity position marker.

Neural networks : the official journal of the International Neural Network Society
A significant amount of textual data has been produced in the biomedical area recently as a result of the advancement of biomedical technologies. Large-scale biomedical data can be automatically obtained with the help of distant supervision. However,...

Embedding-based terminology expansion via secondary use of large clinical real-world datasets.

Journal of biomedical informatics
A log-likelihood based co-occurrence analysis of ∼1.9 million de-identified ICD-10 codes and related short textual problem list entries generated possible term candidates at a significance level of p<0.01. These top 10 term candidates, consisting of ...

Neither neural networks nor the language-of-thought alone make a complete game.

The Behavioral and brain sciences
Cognitive science has evolved since early disputes between radical empiricism and radical nativism. The authors are reacting to the revival of radical empiricism spurred by recent successes in deep neural network (NN) models. We agree that language-l...

Toward biologically plausible artificial vision.

The Behavioral and brain sciences
Quilty-Dunn et al. argue that deep convolutional neural networks (DCNNs) optimized for image classification exemplify structural disanalogies to human vision. A different kind of artificial vision - found in reinforcement-learning agents navigating a...

Extrapolation of affective norms using transformer-based neural networks and its application to experimental stimuli selection.

Behavior research methods
Data on the emotionality of words is important for the selection of experimental stimuli and sentiment analysis on large bodies of text. While norms for valence and arousal have been thoroughly collected in English, most languages do not have access ...

Assessing the accuracy and completeness of artificial intelligence language models in providing information on methotrexate use.

Rheumatology international
We aimed to assess Large Language Models (LLMs)-ChatGPT 3.5-4, BARD, and Bing-in their accuracy and completeness when answering Methotrexate (MTX) related questions for treating rheumatoid arthritis. We employed 23 questions from an earlier study rel...

Performance of ChatGPT-4 in answering questions from the Brazilian National Examination for Medical Degree Revalidation.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: The aim of this study was to evaluate the performance of ChatGPT-4.0 in answering the 2022 Brazilian National Examination for Medical Degree Revalidation (Revalida) and as a tool to provide feedback on the quality of the examination.

A novel Data and Model Centric artificial intelligence based approach in developing high-performance Named Entity Recognition for Bengali Language.

PloS one
Named Entity Recognition (NER) plays a significant role in enhancing the performance of all types of domain specific applications in Natural Language Processing (NLP). According to the type of application, the goal of NER is to identify target entiti...

The use of artificial intelligence to improve the scientific writing of non-native english speakers.

Revista da Associacao Medica Brasileira (1992)
OBJECTIVE: Scientific writing in English is a daunting task for non-native English speakers. The challenges of writing in a foreign language are evident in the scientific literature where texts by non-native English-speaking scientists tend to be les...