AIMC Topic: Humans

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The impact and return-on-investment of evidence-based practice in conservation and environmental management: A machine learning-assisted scoping review protocol.

PloS one
Evidence-based Practice (EBP) is a vital principle, with its origins in the 1970s, that has transformed the disciplines of medicine and healthcare. The use of best available evidence to inform decisions and best practice has since spread across other...

Novel insights from comprehensive analysis: The role of cuproptosis and peripheral immune infiltration in Alzheimer's disease.

PloS one
BACKGROUND: Cuproptosis is increasingly recognized as an essential factor in the pathological process of Alzheimer's disease (AD). However, the specific role of cuproptosis-related genes in AD remains poorly understood.

Application of IRSA-BP neural network in diagnosing diabetes.

PloS one
Within the healthcare sector, the application of machine learning is gaining prominence, notably enhancing the efficiency and precision of diagnostic procedures. This study focuses on this key area of diabetes prediction and aims to develop an innova...

Predicting enamel depth distribution of maxillary teeth based on intraoral scanning: A machine learning study.

Journal of prosthodontic research
PURPOSE: Measuring enamel depth distribution (EDD) is of great importance for preoperative design of tooth preparations, restorative aesthetic preview and monitoring enamel wear. But, currently there are no non-invasive methods available to efficient...

An assessment of generative artificial intelligence in responding to clinical queries on tapering antidepressants.

Research in social & administrative pharmacy : RSAP
BACKGROUND: A substantial cohort of individuals rely on online resources, such as discussion forums, for support on tapering antidepressants. This study aimed to assess the performance of generative artificial intelligence (AI) in responding to clini...

A lightweight spiking neural network for EEG-based motor imagery classification.

Neural networks : the official journal of the International Neural Network Society
Spiking neural networks (SNNs) aim to simulate the human brain neural network, using sparse spike event streams for effective and energy-efficient spatio-temporal signal processing. This paper proposes a lightweight SNN model for electroencephalogram...

CTFS: A consolidated transformer framework for instance and semantic segmentation tasks.

Neural networks : the official journal of the International Neural Network Society
Instance segmentation and semantic segmentation are fundamental tasks that support many computer vision applications. Recently, researchers have investigated the feasibility of constructing a unified transformer framework and leveraging multi-task le...

The Cost Outcome Pathway framework: Integrating socio-economic impacts to Adverse Outcome Pathways for supporting policy makers.

Toxicology
The Adverse Outcome Pathway (AOP) concept leverages existing data to formalize and disseminate knowledge and is a well-accepted concept in chemical risk assessment. However, it does not handle the socio-economic impact that environmentally-induced di...

Sequence and Structure-based Prediction of Allosteric Sites.

Journal of molecular biology
Allosteric regulation in proteins is a critical aspect of cellular function, influencing various biological processes through conformational or dynamic changes induced by effector molecules. Allosteric drugs possess significant therapeutic value due ...

GraphCF: Drug-target interaction prediction via multi-feature fusion with contrastive graph neural network.

Artificial intelligence in medicine
Drug-target interaction (DTI) is paramount in drug discovery and repurposing, which involves screening for effective candidate drugs by targeting specific proteins. Existing methods often focus on one or two representations of drugs or targets, and l...