AIMC Topic: Neural Networks, Computer

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Lightweight hybrid transformers-based dyslexia detection using cross-modality data.

Scientific reports
Early and precise diagnosis of dyslexia is crucial for implementing timely intervention to reduce its effects. Timely identification can improve the individual's academic and cognitive performance. Traditional dyslexia detection (DD) relies on length...

Multi-filter based signed heterogeneous graph convolutional networks for predicting activating/inhibiting drug-target interactions.

Methods (San Diego, Calif.)
The prediction of mechanisms within drug-target interactions (DTIs) can boost the drug discovery process, which has traditionally relied on time-consuming and expensive laboratory experiments. Despite much more attention has been paid to predicting D...

Modeling and Optimization of Recombinant Tocilizumab Production From Pichia pastoris Using Response Surface Methodology and Artificial Neural Network.

Biotechnology and bioengineering
This study has demonstrated the optimization of the defined medium that significantly enhanced the production of recombinant monoclonal antibody (mAb) Tocilizumab (TCZ) as full-length and Fab fragment from Pichia pastoris. Out of the four tested defi...

A monocular endoscopic image depth estimation method based on a window-adaptive asymmetric dual-branch Siamese network.

Scientific reports
Minimally invasive surgery involves entering the body through small incisions or natural orifices, using a medical endoscope for observation and clinical procedures. However, traditional endoscopic images often suffer from low texture and uneven illu...

Automated high precision PCOS detection through a segment anything model on super resolution ultrasound ovary images.

Scientific reports
PCOS (Poly-Cystic Ovary Syndrome) is a multifaceted disorder that often affects the ovarian morphology of women of their reproductive age, resulting in the development of numerous cysts on the ovaries. Ultrasound imaging typically diagnoses PCOS, whi...

Early detection of Alzheimer's disease progression stages using hybrid of CNN and transformer encoder models.

Scientific reports
Alzheimer's disease (AD) is a neurodegenerative disorder that affects memory and cognitive functions. Manual diagnosis is prone to human error, often leading to misdiagnosis or delayed detection. MRI techniques help visualize the fine tissues of the ...

Parvalbumin neurons and cortical coding of dynamic stimuli: a network model.

Journal of neurophysiology
Cortical circuits feature both excitatory and inhibitory cells that underlie the encoding of dynamic sensory stimuli, e.g., speech, music, odors, and natural scenes. Although previous studies have shown that inhibition plays an important role in shap...

A comparative analysis of logistic regression (LR) and artificial neural network (ANN) models for predicting antimicrobial resistance in surgical ICU patients: Insights from real-world evidence in India.

The International journal of risk & safety in medicine
BackgroundMachine learning approaches for the prediction of antimicrobial resistance (AMR) are gaining attention but are yet to be commonly applied in practice.ObjectiveThis study aims to predict the AMR in surgical intensive care unit patients using...

A Genetic Algorithms-Based Neural Network Model to Monitor Gibberellic Acid GA3 Fermentation Process by Fusarium fujikuroi.

Biotechnology and bioengineering
A genetic algorithm-optimized neural network (ANN-GA) was developed for real-time monitoring of gibberellin (GA3) production during Fusarium fujikuroi fermentation. This model addresses the limitations of traditional off-line detection methods, such ...

Development and validation of a collaborative framework for assessment of peripheral facial paralysis using facial image regions of interest.

Acta oto-laryngologica
BACKGROUND: While accurate evaluation of PFP is crucial for determining optimal treatment strategies, current clinical assessments rely heavily on subjective evaluations, leading to considerable variability between inter- and intra-observer ratings.