AIMC Topic: Humans

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Unveiling factors influencing judgment variation in sentiment analysis with natural language processing and statistics.

PloS one
TripAdvisor reviews and comparable data sources play an important role in many tasks in Natural Language Processing (NLP), providing a data basis for the identification and classification of subjective judgments, such as hotel or restaurant reviews, ...

Application of a transparent artificial intelligence algorithm for US adults in the obese category of weight.

PloS one
OBJECTIVE AND AIMS: Identification of associations between the obese category of weight in the general US population will continue to advance our understanding of the condition and allow clinicians, providers, communities, families, and individuals m...

Visual explanations for polyp detection: How medical doctors assess intrinsic versus extrinsic explanations.

PloS one
Deep learning has achieved immense success in computer vision and has the potential to help physicians analyze visual content for disease and other abnormalities. However, the current state of deep learning is very much a black box, making medical pr...

Machine learning prediction of nutritional status among pregnant women in Bangladesh: Evidence from Bangladesh demographic and health survey 2017-18.

PloS one
AIM: Malnutrition in pregnant women significantly affects both mother and child health. This research aims to identify the best machine learning (ML) techniques for predicting the nutritional status of pregnant women in Bangladesh and detect the most...

Expansive data, extensive model: Investigating discussion topics around LLM through unsupervised machine learning in academic papers and news.

PloS one
This study presents a comprehensive exploration of topic modeling methods tailored for large language model (LLM) using data obtained from Web of Science and LexisNexis from June 1, 2020, to December 31, 2023. The data collection process involved que...

Mapping automatic social media information disorder. The role of bots and AI in spreading misleading information in society.

PloS one
This paper presents an analysis on information disorder in social media platforms. The study employed methods such as Natural Language Processing, Topic Modeling, and Knowledge Graph building to gain new insights into the phenomenon of fake news and ...

Classifying Routine Clinical Electroencephalograms With Multivariate Iterative Filtering and Convolutional Neural Networks.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Electroencephalogram (EEG) is widely used in basic and clinical neuroscience to explore neural states in various populations, and classifying these EEG recordings is a fundamental challenge. While machine learning shows promising results in classifyi...

Verbal behavior and the future of social science.

The American psychologist
Natural language processing (NLP)-previously the domain of a select few language and computer scientists-is undergoing an unprecedented surge in popularity across disciplines. The ubiquity of language data, alongside extremely rapid methodological in...

Using drawings and deep neural networks to characterize the building blocks of human visual similarity.

Memory & cognition
Early in life and without special training, human beings discern resemblance between abstract visual stimuli, such as drawings, and the real-world objects they represent. We used this capacity for visual abstraction as a tool for evaluating deep neur...