AIMC Topic: Humans

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An automated classification pipeline for tables in pharmacokinetic literature.

Scientific reports
Pharmacokinetic (PK) models are essential for optimising drug candidate selection and dosing regimens in drug development. Preclinical and population PK models benefit from integrating prior knowledge from existing compounds. While tables in scientif...

A deep learning model based on Mamba for automatic segmentation in cervical cancer brachytherapy.

Scientific reports
This study developed and evaluated an automatic segmentation model based on the Mamba framework (AM-UNet) for rapid and precise delineation of high-risk clinical target volume (HRCTV) and organs at risk (OARs) in cervical cancer brachytherapy. Using ...

AI optimization algorithms enhance higher education management and personalized teaching through empirical analysis.

Scientific reports
This research investigates the application of artificial intelligence (AI) optimization algorithms in higher education management and personalized teaching. Through a comprehensive literature review, theoretical analysis, and empirical study, the pot...

Two-tier nature inspired optimization-driven ensemble of deep learning models for effective autism spectrum disorder diagnosis in disabled persons.

Scientific reports
Autism spectrum disorder (ASD) includes a varied set of neuropsychiatric illnesses. This disorder is described by a definite grade of loss in social communication, academic functioning, personal contact, and limited and repetitive behaviours. Individ...

Employing artificial bee and ant colony optimization in machine learning techniques as a cognitive neuroscience tool.

Scientific reports
Higher education is essential because it exposes students to a variety of areas. The academic performance of IT students is crucial and might fail if it isn't documented to identify the features influencing them, as well as their strengths and shortc...

Using machine learning to simultaneously quantify multiple cognitive components of episodic memory.

Nature communications
Why do we remember some events but forget others? Previous studies attempting to decode successful vs. unsuccessful brain states to investigate this question have met with limited success, potentially due, in part, to assessing episodic memory as a u...

Early prediction of intraventricular hemorrhage in very low birth weight infants using deep neural networks with attention in low-resource settings.

Scientific reports
Early prediction of intraventricular hemorrhage (IVH) in very low-birthweight infants (VLBWIs) remains challenging because of multifactorial risk factors. IVH often occurs within a few hours after birth, yet its onset cannot be reliably predicted usi...

Bio-inspired neural networks with central pattern generators for learning multi-skill locomotion.

Scientific reports
Biological neural circuits, central pattern generators (CPGs), located at the spinal cord are the underlying mechanisms that play a crucial role in generating rhythmic locomotion patterns. In this paper, we propose a novel approach that leverages the...

Machine learning prediction of premature death from multimorbidity among people with inflammatory bowel disease: a population-based retrospective cohort study.

CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
BACKGROUND: Multimorbidity, the co-occurrence of 2 or more chronic conditions, is important in patients with inflammatory bowel disease (IBD) given its association with complex care plans, poor health outcomes, and excess mortality. Our objectives we...