AIMC Topic: Neural Networks, Computer

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Recurrent Neural Networks Predict Future Peptide Aggregation for Drug Development.

Molecular pharmaceutics
Physical stability of an active pharmaceutical ingredient (API) is a key consideration in the development of a pharmaceutical drug. Solution conditions such as pH, excipient concentrations, and storage temperatures can impact the physical stability o...

Evaluating vision transformers and convolutional neural networks in the context of dental image processing: a systematic review.

BMC oral health
BACKGROUND: The aim of this systematic review is to compare the efficacy of convolutional neural networks (CNN) and Vision Transformers (ViT) in the field of dental imaging, in order to examine in depth the potential, advantages, and limitations of b...

DCMF-PPI: a protein-protein interaction predictor based on dynamic condition and multi-feature fusion.

BMC bioinformatics
BACKGROUND: The identification of protein-protein interaction (PPI) plays a crucial role in understanding the mechanisms of complex biological processes. Current research in predicting PPI has shown remarkable progress by integrating protein informat...

A neuro-fuzzy model for evaluating and predicting computational thinking skills of students.

Scientific reports
Computational thinking skill is an important skill individuals should acquire to meet the requirements of the digital age. The aim of the study is to predict the computational thinking skills of middle school students through ANFIS approach, which is...

Enhanced backpropagation neural network accuracy through an improved genetic algorithm for tourist flow prediction in an ecological village.

Scientific reports
Extant tourism studies on predicting tourist flow often adopt Backpropagation Neural Network (BP-NN) and Genetic Algorithm-Backpropagation Neural Network (GABP-NN). However, those models cannot well address the challenge of nonlinear complexity of to...

Child behavior recognition in social robot interaction using stacked deep neural networks and biomechanical signals.

Scientific reports
With the growing integration of social robots into pediatric environments, understanding and monitoring child-robot interaction has become increasingly important. Toward the advancement of biomechanical monitoring systems for pediatric applications, ...

Privacy preserving skin cancer diagnosis through federated deep learning and explainable AI.

Scientific reports
The classification of human skin disorders, particularly benign and malignant skin cancer, is thoroughly examined in this study with a focus on protecting data privacy. Traditional visual diagnosis of skin disorders is often subjective and complicate...

Efficient hybrid fuzzy weighted 3D FCNN with TSO PSO optimization for accurate multi modal MRI brain tumor classification.

Scientific reports
Detecting and segmenting brain tumors from 3D MRI images is a challenging and time-intensive task for clinicians. This research introduces an innovative hybrid architecture for deep learning, comprising a 3D fully convolutional neural network (3D-FCN...

Artificial embodied circuits uncover neural architectures of vertebrate visuomotor behaviors.

Science robotics
Brains evolve within specific sensory and physical environments, yet neuroscience has traditionally focused on studying neural circuits in isolation. Understanding of their function requires integrative brain-body testing in realistic contexts. To in...

Analysis of Breast Cancer Information on Facebook Using Neural Network-Based Topic Modeling and Metadata Analysis of English and Spanish Content: Comparative Study.

Journal of medical Internet research
BACKGROUND: Breast cancer is the most common cancer diagnosis among women, with approximately 2.3 million new cases annually. When faced with a cancer diagnosis, individuals often turn to the internet for information or reassurance, despite the risk ...