AIMC Topic: Learning

Clear Filters Showing 381 to 390 of 1476 articles

iHerd: an integrative hierarchical graph representation learning framework to quantify network changes and prioritize risk genes in disease.

PLoS computational biology
Different genes form complex networks within cells to carry out critical cellular functions, while network alterations in this process can potentially introduce downstream transcriptome perturbations and phenotypic variations. Therefore, developing e...

Integrating Reaction Schemes, Reagent Databases, and Virtual Libraries into Fragment-Based Design by Reinforcement Learning.

Journal of chemical information and modeling
Lead optimization supported by artificial intelligence (AI)-based generative models has become increasingly important in drug design. Success factors are reagent availability, novelty, and the optimization of multiple properties. Directed fragment-re...

On exploring node-feature and graph-structure diversities for node drop graph pooling.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have been successfully applied to graph-level tasks in various fields such as biology, social networks, computer vision, and natural language processing. For the graph-level representations learning of GNNs, graph pooling...

Artificial intelligence-assisted dermatology diagnosis: From unimodal to multimodal.

Computers in biology and medicine
Artificial Intelligence (AI) is progressively permeating medicine, notably in the realm of assisted diagnosis. However, the traditional unimodal AI models, reliant on large volumes of accurately labeled data and single data type usage, prove insuffic...

Adaptive optimal control of affine nonlinear systems via identifier-critic neural network approximation with relaxed PE conditions.

Neural networks : the official journal of the International Neural Network Society
This paper considers an optimal control of an affine nonlinear system with unknown system dynamics. A new identifier-critic framework is proposed to solve the optimal control problem. Firstly, a neural network identifier is built to estimate the unkn...

Effects of Motion-Relevant Knowledge From Unlabeled Video to Human-Object Interaction Detection.

IEEE transactions on neural networks and learning systems
The existing works on human-object interaction (HOI) detection usually rely on expensive large-scale labeled image datasets. However, in real scenes, labeled data may be insufficient, and some rare HOI categories have few samples. This poses great ch...

ChatGPT and Generative Artificial Intelligence for Medical Education: Potential Impact and Opportunity.

Academic medicine : journal of the Association of American Medical Colleges
ChatGPT has ushered in a new era of artificial intelligence (AI) that already has significant consequences for many industries, including health care and education. Generative AI tools, such as ChatGPT, refer to AI that is designed to create or gener...

A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational cost.

Science advances
Neuromodulators in the brain act globally at many forms of synaptic plasticity, represented as metaplasticity, which is rarely considered by existing spiking (SNNs) and nonspiking artificial neural networks (ANNs). Here, we report an efficient brain-...

Innovations in surgical training: exploring the role of artificial intelligence and large language models (LLM).

Revista do Colegio Brasileiro de Cirurgioes
The landscape of surgical training is rapidly evolving with the advent of artificial intelligence (AI) and its integration into education and simulation. This manuscript aims to explore the potential applications and benefits of AI-assisted surgical ...

Comparing feedforward neural networks using independent component analysis on hidden units.

PloS one
Neural networks are widely used for classification and regression tasks, but they do not always perform well, nor explicitly inform us of the rationale for their predictions. In this study we propose a novel method of comparing a pair of different fe...