AIMC Topic: Learning

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Generating meaning: active inference and the scope and limits of passive AI.

Trends in cognitive sciences
Prominent accounts of sentient behavior depict brains as generative models of organismic interaction with the world, evincing intriguing similarities with current advances in generative artificial intelligence (AI). However, because they contend with...

On effectively predicting autism spectrum disorder therapy using an ensemble of classifiers.

Scientific reports
An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking question is whether such an ensemble can outperform the single best classifier. If so, what form of ens...

MECCH: Metapath Context Convolution-based Heterogeneous Graph Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Heterogeneous graph neural networks (HGNNs) were proposed for representation learning on structural data with multiple types of nodes and edges. To deal with the performance degradation issue when HGNNs become deep, researchers combine metapaths into...

Assessment of the capacity of ChatGPT as a self-learning tool in medical pharmacology: a study using MCQs.

BMC medical education
BACKGROUND: ChatGPT is a large language model developed by OpenAI that exhibits a remarkable ability to simulate human speech. This investigation attempts to evaluate the potential of ChatGPT as a standalone self-learning tool, with specific attentio...

CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures.

Nature communications
The field of bioimage analysis is currently impacted by a profound transformation, driven by the advancements in imaging technologies and artificial intelligence. The emergence of multi-modal AI systems could allow extracting and utilizing knowledge ...

Deep learning-based 3D brain multimodal medical image registration.

Medical & biological engineering & computing
Medical image registration is a critical preprocessing step in medical image analysis. While traditional medical image registration techniques have matured, their registration speed and accuracy still fall short of clinical requirements. In this pape...

Examining ChatGPT Performance on USMLE Sample Items and Implications for Assessment.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: In late 2022 and early 2023, reports that ChatGPT could pass the United States Medical Licensing Examination (USMLE) generated considerable excitement, and media response suggested ChatGPT has credible medical knowledge. This report analyzes...

Self-supervised multi-modal training from uncurated images and reports enables monitoring AI in radiology.

Medical image analysis
The escalating demand for artificial intelligence (AI) systems that can monitor and supervise human errors and abnormalities in healthcare presents unique challenges. Recent advances in vision-language models reveal the challenges of monitoring AI by...

Leveraging spatial residual attention and temporal Markov networks for video action understanding.

Neural networks : the official journal of the International Neural Network Society
The effective use of temporal relationships while extracting fertile spatial features is the key to video action understanding. Video action understanding is a challenging visual task because it generally necessitates not only the features of individ...

The development of robotics courses for young children under vector space model.

PloS one
Robotics education is important in training children's thinking, practical, and innovation abilities. It is significant to stimulate children's interest in learning and improve their learning quality. The existing research has not paid attention to t...