AIMC Topic: Humans

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Artificial intelligence and large language models in palliative medicine clinical practice and education.

BMJ supportive & palliative care
As we approach 2034, we anticipate significant advancements in digital technologies and their impact across various domains, including palliative and end-of-life care and perhaps higher education more generally. Predicting technological breakthroughs...

AI-generated estimates of familiarity, concreteness, valence, and arousal for over 100,000 Spanish words.

Quarterly journal of experimental psychology (2006)
This study investigates whether estimates of familiarity, valence, arousal, and concreteness based on artificial intelligence (AI) are useful alternatives to word counts and human ratings in Spanish. We replicate and extend previous findings in Engli...

Value of the combination of intraepithelial tumor-infiltrating lymphocyte density and the heterogeneity of density as a prognostic marker in stage III colorectal cancers.

Histology and histopathology
Tumor-infiltrating lymphocyte (TIL) density is both a prognostic and a predictive factor in colorectal cancer (CRC). Whether the heterogeneity of TIL density across the tumor plays an important role in the clinical outcome of CRC is not well known. A...

Unveiling predictive factors for household-level stunting in India: A machine learning approach using NFHS-5 and satellite-driven data.

Nutrition (Burbank, Los Angeles County, Calif.)
OBJECTIVES: Childhood stunting remains a significant public health issue in India, affecting approximately 35% of children under 5. Despite extensive research, existing prediction models often fail to incorporate diverse data sources and address the ...

Learnable color space conversion and fusion for stain normalization in pathology images.

Medical image analysis
Variations in hue and contrast are common in H&E-stained pathology images due to differences in slide preparation across various institutions. Such stain variations, while not affecting pathologists much in diagnosing the biopsy, pose significant cha...

Multi-modal cross-domain self-supervised pre-training for fMRI and EEG fusion.

Neural networks : the official journal of the International Neural Network Society
Neuroimaging techniques including functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) have shown promise in detecting functional abnormalities in various brain disorders. However, existing studies often focus on a single domai...

On the probability of necessity and sufficiency of explaining Graph Neural Networks: A lower bound optimization approach.

Neural networks : the official journal of the International Neural Network Society
The explainability of Graph Neural Networks (GNNs) is critical to various GNN applications, yet it remains a significant challenge. A convincing explanation should be both necessary and sufficient simultaneously. However, existing GNN explaining appr...

Heterophilous distribution propagation for Graph Neural Networks.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have achieved remarkable success in various graph mining tasks by aggregating information from neighborhoods for representation learning. The success relies on the homophily assumption that nearby nodes exhibit similar be...

Unified Knowledge-Guided Molecular Graph Encoder with multimodal fusion and multi-task learning.

Neural networks : the official journal of the International Neural Network Society
The remarkable success of Graph Neural Networks underscores their formidable capacity to assimilate multimodal inputs, markedly enhancing performance across a broad spectrum of domains. In the context of molecular modeling, considerable efforts have ...

Promises and perils of using Transformer-based models for SE research.

Neural networks : the official journal of the International Neural Network Society
Many Transformer-based pre-trained models for code have been developed and applied to code-related tasks. In this paper, we analyze 519 papers published on this topic during 2017-2023, examine the suitability of model architectures for different task...