AIMC Topic: Humans

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Clinical Risk Computation by Large Language Models Using Validated Risk Scores.

Journal of medical systems
Recent advances in artificial intelligence have propelled Large Language Models (LLMs) in natural language understanding, enabling new healthcare applications. While LLMs can analyze health data, directly predicting patient risk scores can be unrelia...

A Pretraining Approach for Small-sample Training Employing Radiographs (PASTER): a Multimodal Transformer Trained by Chest Radiography and Free-text Reports.

Journal of medical systems
While deep convolutional neural networks (DCNNs) have achieved remarkable performance in chest X-ray interpretation, their success typically depends on access to large-scale, expertly annotated datasets. However, collecting such data in real-world cl...

TFDISNet: Temporal-frequency domain-invariant and domain-specific feature learning network for enhanced auditory attention decoding from EEG signals.

Biomedical physics & engineering express
Auditory Attention Decoding (AAD) from Electroencephalogram (EEG) signals presents a significant challenge in brain-computer interface (BCI) research due to the intricate nature of neural patterns. Existing approaches often fail to effectively integr...

Hybrid-MedNet: a hybrid CNN-transformer network with multi-dimensional feature fusion for medical image segmentation.

Physics in medicine and biology
Twin-to-twin transfusion syndrome (TTTS) is a complex prenatal condition in which monochorionic twins experience an imbalance in blood flow due to abnormal vascular connections in the shared placenta. Fetoscopic laser photocoagulation is the first-li...

Assessing the feasibility of deep learning-based attenuation correction using photon emission data inF-FDG images for dedicated head and neck PET scanners.

Biomedical physics & engineering express
This study aimed to evaluate the use of deep learning techniques to produce measured attenuation-corrected (MAC) images from non-attenuation-corrected (NAC) F-FDG PET images, focusing on head and neck imaging. A Residual Network (ResNet) was used to ...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.

Journal of neural engineering
Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as mild cognitive impairment (MCI), where patients may either progress to AD or remain stable. The objective of the work was to capture st...

Spatial distribution patterns and risk factors of hookworm disease in China: A study based on successive national surveillance.

PLoS neglected tropical diseases
BACKGROUND: Hookworm infection, a neglected tropical disease (NTD) causing iron-deficiency anaemia and malnutrition in low-income populations with poor sanitation, poses a considerable public health challenge in China and worldwide.

Mathematical models for predicting the toxicity of micropollutant mixtures in water.

Arhiv za higijenu rada i toksikologiju
Water pollution caused by micropollutants has been a global issue for decades, prompting the scientific community and industry professionals to develop new and effective wastewater treatment methods. Understanding the interactions of these compounds ...

Integrating AI in Pakistani ESL classrooms: Teachers' practices, perspectives, and impact on student performance.

PloS one
The global rise of Artificial Intelligence (AI) in English as a Second Language (ESL) education has shown promise, yet its application in resource-constrained contexts like Pakistan remains underexplored. This study examines the integration of AI too...

Predictive modeling of tax compliance risks: A comparative study of machine learning approaches.

PloS one
Modern enterprises grapple with complex financial data and multidimensional risk interdependencies in their operations. Machine learning offers transformative potential for tax risk assessment and smart auditing solutions. This research analyzes 3,23...