AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Learning

Showing 301 to 310 of 1361 articles

Clear Filters

A scalable second order optimizer with an adaptive trust region for neural networks.

Neural networks : the official journal of the International Neural Network Society
We introduce Tadam (Trust region ADAptive Moment estimation), a new optimizer based on the trust region of the second-order approximation of the loss using the Fisher information matrix. Despite the enhanced gradient estimations offered by second-ord...

Learning heterogeneous delays in a layer of spiking neurons for fast motion detection.

Biological cybernetics
The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiolo...

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-...