AIMC Topic: Humans

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Eye movement detection using electrooculography and machine learning in cardiac arrest patients.

Resuscitation
AIM: To train a machine learning algorithm to identify eye movement from electrooculography (EOG) in cardiac arrest (CA) patients. Neuroprognostication of comatose post-CA patients is challenging, requiring novel biomarkers to guide decision making. ...

Synergistic eigenanalysis of covariance and Hessian matrices for enhanced binary classification on health datasets.

Computers in biology and medicine
Covariance and Hessian matrices have been analyzed separately in the literature for classification problems. However, integrating these matrices has the potential to enhance their combined power in improving classification performance. We present a n...

Leveraging Transfer Learning for Predicting Protein-Small-Molecule Interaction Predictions.

Journal of chemical information and modeling
A complex web of intermolecular interactions defines and regulates biological processes. Understanding this web has been particularly challenging because of the sheer number of actors in biological systems: ∼10 proteins in a typical human cell offer ...

Mechanistic Study of Protein Interaction with Natto Inhibitory Peptides Targeting Xanthine Oxidase: Insights from Machine Learning and Molecular Dynamics Simulations.

Journal of chemical information and modeling
Bioactive peptides from food sources offer a safe and biocompatible approach to enzyme inhibition, with potential applications in managing metabolic disorders such as hyperuricemia and gout, conditions linked to excessive xanthine oxidase activity. U...

The AI-environment paradox: Unraveling the impact of artificial intelligence (AI) adoption on pro-environmental behavior through work overload and self-efficacy in AI learning.

Journal of environmental management
This study examines the complex relationships among artificial intelligence (AI) adoption in organizations, employee work overload, and pro-environmental behavior at work (PEBW), while examining the moderating role of self-efficacy in AI learning. Dr...

Phase of firing does not reflect temporal order in sequence memory of humans and recurrent neural networks.

Nature neuroscience
The temporal order of a sequence of events has been thought to be reflected in the ordered firing of neurons at different phases of theta oscillations. Here we assess this by measuring single neuron activity (1,420 neurons) and local field potentials...

The good, the bad, and the binary: Ethical impact of AI on nursing practice.

Nursing
Artificial intelligence (AI) promises significant advancements in patient care, burden reduction, and nursing efficiency. This article examines the multifaceted impact of AI on nursing practice; its benefits and potential ethical issues; and ways for...

Artificial intelligence in nursing: A journey from data to wisdom.

Nursing
Artificial intelligence (AI) can enhance nursing practice by assisting in clinical decisions, patient outcomes, and operational efficiencies. This article explores the role of AI in decision-making, data management, and task automation within the Dat...

Machine Learning-Based VO Estimation Using a Wearable Multiwavelength Photoplethysmography Device.

Biosensors
The rate of oxygen consumption, which is measured as the volume of oxygen consumed per mass per minute (VO) mL/kg/min, is a critical metric for evaluating cardiovascular health, metabolic status, and respiratory function. Specifically, VO is a powerf...

Reasoning-Driven Food Energy Estimation via Multimodal Large Language Models.

Nutrients
Image-based food energy estimation is essential for user-friendly food tracking applications, enabling individuals to monitor their dietary intake through smartphones or AR devices. However, existing deep learning approaches struggle to recognize a ...