eLife

A differentiable model for optimizing the genetic drivers of synaptogenesis

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
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Backpropagation in neural networks step-by-step explained

Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back ...
Open Heart

Development and validation of a deep learning model for severe mitral stenosis detection from chest X-rays

Background Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains ...
IEEE

Short and Medium-Term Power Load Anomaly Detection Method Based on Convolutional Neural Network and EL-DCC

Abstract: Power load anomaly detection is critical to grid stability and security. With the increasing complexity of load patterns, it is difficult for traditional methods to meet the requirements of ...

How AI coding agents work—and what to remember if you use them

At the core of every AI coding agent is a technology called a large language model (LLM), which is a type of neural network ...
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Python neural network for multiclass classification using softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by ...
IEEE

Collating Random Forest Classifier and Artificial Neural Networks for the Risk Detection of Maternal Health

Abstract: This paper compares the performance of ANN models to Random Forests on benchmarking a test dataset against the risk levels of maternal health as low, mid, or high. The features considered ...