Latest AI and machine learning research in identifying and reporting child abuse for healthcare professionals.
An accurate energy scoring function is crucial for protein structure prediction. Given the increasing number of experimentally determined structures, knowledge-based approaches have been widely used to develop scoring functions for protein structure prediction in the past three decades. However, current scoring functions often only consider nonbonded interactions and neglect bonded potentials like...
This paper tries to give a gentle introduction to deep learning in medical image processing, proceeding from theoretical foundations to applications. We first discuss general reasons for the popularity of deep learning, including several major breakthroughs in computer science. Next, we start reviewing the fundamental basics of the perceptron and neural networks, along with some fundamental theory...
Disease progression modeling (DPM) using longitudinal data is a challenging machine learning task. Existing DPM algorithms neglect temporal dependenci...
Low-rank representation (LRR) has aroused much attention in the community of data mining. However, it has the following twoproblems which greatly limi...
Understanding genetic mechanism of complex diseases is a serious challenge. Existing methods often neglect the heterogeneity phenomenon of complex dis...
The hippocampus is a highly stress susceptible structure and hippocampal abnormalities have been reported in a host of psychiatric disorders including...
Air pollutant concentration forecasting is an effective method of protecting public health by providing an early warning against harmful air pollutant...
With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis ...
The identification of drug target proteins (IDTP) plays a critical role in biometrics. The aim of this study was to retrieve potential drug target pro...
In this paper, we present the experimental results of an embodied cognitive robotic approach for modelling the human cognitive deficit known as unilat...
Quantitative descriptions of network structure can provide fundamental insights into the function of interconnected complex systems. Small-world struc...
The eigenvalue spectrum of the matrix of directed weights defining a neural network model is informative of several stability and dynamical properties...
Image-based 3D visual grounding is critical for embodied agents, yet existing benchmarks suffer from loose text-observation alignment and neglect temp...
Recently, the rapid advancement of multimodal domains has driven a data-centric paradigm shift in graph ML, transitioning from text-attributed to mult...
Existing diffusion-based methods have recently made significant progress in image dehazing. However, they typically neglect the physics of haze format...
The continuous accumulation of genetic mutations in influenza A viruses (IAVs) drives antigenic drift, necessitating precise antigenic prediction for ...
The rapid advancement of image generation models has made it increasingly difficult for people to distinguish AI-generated images from real ones. To p...
Recent advances in 3D Gaussian Splatting (3DGS)-based wireless radiance field (WRF) reconstruction provide an efficient solution for wireless channel ...
Enhancing classification performance in mammography remains a persistent challenge across both small curated datasets and large-scale clinical cohorts...
Affective Image Content Analysis (AICA) aims to recognize and understand emotions elicited by visual content, representing an indispensable step towar...