Synthesizing the best material globally is challenging; it needs to know what and how much the best ingredient composition should be for satisfying multiple figures of merit simultaneously. Traditional one-variable-at-a-time methods are inefficient; ...
Molecular Biology has long tried to discover mechanisms, considering that unless we understand the principles, we cannot develop applications. Now machine learning and artificial intelligence enable direct leaps to application without understanding t...
Nowadays, wireless sensor networks (WSN) have gained huge attention worldwide due to their wide applications in different domains. The limited amount of energy resources is considered as the main limitations of WSN, which generally affect the network...
PURPOSE: Due to the existence of information opacity, there is a common problem of adverse selection in the process of screening alternative technology start-ups (TSs) and determining investment targets by venture capital institutions, which does not...
To further enhance the residual current detection capability of low-voltage distribution networks, an improved adaptive residual current detection method that combines variational modal decomposition (VMD) and BP neural network (BPNN) is proposed. Fi...
This article proposes a continuous-time optimization approch instead of tranditional optimiztion methods to address the nuclear norm minimization (NNM) problem. Refomulating the NNM into a matrix form, we propose a Lagrangian programming neural netwo...
To accurately locate faulty components in analog circuits, an analog circuit fault diagnosis method based on Tunable Q-factor Wavelet Transform(TQWT) and Convolutional Neural Network (CNN) is proposed in this paper. Firstly, the Grey Wolf algorithm (...
Journal of ISAKOS : joint disorders & orthopaedic sports medicine
Feb 7, 2024
Machine learning (ML) is changing the way health care is practiced and recent applications of these novel statistical techniques have started to impact orthopaedic sports medicine. Machine learning enables the analysis of large volumes of data to est...
This study introduces AIEgen-Deep, an innovative classification program combining AIEgen fluorescent dyes, deep learning algorithms, and the Segment Anything Model (SAM) for accurate cancer cell identification. Our approach significantly reduces manu...
Protein-protein interactions (PPIs) are pivotal for driving diverse biological processes, and any disturbance in these interactions can lead to disease. Thus, the study of PPIs has been a central focus in biology. Recent developments in deep learning...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.