AI Medical Compendium Topic

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Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing.

PloS one
In order to accurately assess the students' learning process and the cognitive state of knowledge points in smart classroom. A classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing model (CL-PTKT...

Knowledge-Guided Semantically Consistent Contrastive Learning for sequential recommendation.

Neural networks : the official journal of the International Neural Network Society
Contrastive learning has gained dominance in sequential recommendation due to its ability to derive self-supervised signals for addressing data sparsity problems. However, caused by random augmentations (e.g., crop, mask, and reorder), existing metho...

A rule- and query-guided reinforcement learning for extrapolation reasoning in temporal knowledge graphs.

Neural networks : the official journal of the International Neural Network Society
Extrapolation reasoning in temporal knowledge graphs (TKGs) aims at predicting future facts based on historical data, and finds extensive application in diverse real-world scenarios. Existing TKG reasoning methods primarily focus on capturing the fac...

Memory flow-controlled knowledge tracing with three stages.

Neural networks : the official journal of the International Neural Network Society
Knowledge Tracing (KT), as a pivotal technology in intelligent education systems, analyzes students' learning data to infer their knowledge acquisition and predict their future performance. Recent advancements in KT recognize the importance of memory...

Hermeneutics as impediment to AI in medicine.

Theoretical medicine and bioethics
Predictions that artificial intelligence (AI) will become capable of replacing human beings in domains such as medicine rest implicitly on a theory of mind according to which knowledge can be captured propositionally without loss of meaning. Generati...

Dual view graph transformer networks for multi-hop knowledge graph reasoning.

Neural networks : the official journal of the International Neural Network Society
To address the incompleteness of knowledge graphs, multi-hop reasoning aims to find the unknown information from existing data and enhance the comprehensive understanding. The presence of reasoning paths endows multi-hop reasoning with interpretabili...

Bridging the human-AI knowledge gap through concept discovery and transfer in AlphaZero.

Proceedings of the National Academy of Sciences of the United States of America
AI systems have attained superhuman performance across various domains. If the hidden knowledge encoded in these highly capable systems can be leveraged, human knowledge and performance can be advanced. Yet, this internal knowledge is difficult to ex...

Enhancing text-centric fake news detection via external knowledge distillation from LLMs.

Neural networks : the official journal of the International Neural Network Society
Fake news poses a significant threat to society, making the automatic and accurate detection of fake news an urgent task. Various detection cues have been explored in extensive research, with news text content shown to be indispensable as it directly...

AI anxiety and knowledge payment: the roles of perceived value and self-efficacy.

BMC psychology
BACKGROUND: The integration of Artificial Intelligence (AI) into daily life raises significant challenges and uncertainties, notably concerning job security and skill relevance. This has led to the emergence of 'AI anxiety'-a stress response to poten...

Postphenomenological Study: Using Generative Knowing and Science Fiction for Fostering Speculative Reflection on AI-nudge Experience.

Science and engineering ethics
This study presents an evidence-based argument for integrating participatory inquiry practices into AI education, using science fiction films as a primary tool for examining human-technology relationships. Through a media-enhanced co-inquiry approach...