Latest AI and machine learning research in identifying and reporting child abuse for healthcare professionals.
Federated learning has emerged as a key paradigm in privacy-preserving computing due to its "data usable but not visible" property, enabling users to collaboratively train models without sharing raw data. Motivated by this, federated recommendation systems offer a promising architecture that balances user privacy with recommendation accuracy through distributed collaborative learning. However, e...
Knowledge distillation has been widely adopted in computer vision task processing, since it can effectively enhance the performance of lightweight student networks by leveraging the knowledge transferred from cumbersome teacher networks. Most existing knowledge distillation methods utilize Kullback-Leibler divergence to mimic the logit output probabilities between the teacher network and the stu...
Recommender systems aim to provide personalized item recommendations by capturing user behaviors derived from their interaction history. Considering...
To preserve user privacy in recommender systems, federated recommendation (FR) based on federated learning (FL) emerges, keeping the personal data o...
Retinal image registration is vital for diagnostic therapeutic applications within the field of ophthalmology. Existing public datasets, focusing on...
Adolescent major depressive disorder (MDD) is characterized by heterogeneous symptomatology and complex neurodevelopmental underpinnings. Here, we inv...
The common marmoset is an important model in biomedical and clinical research, particularly for the study of age-related, neurodegenerative, and neuro...
N6-methyladenosine (m6A) is a crucial epitranscriptomic mark. While Nanopore Direct RNA Sequencing (DRS) enables transcriptome-wide detection, most ex...
Existing breast cancer risk models inadequately identify individuals at latent risk, particularly among women without known genetic mutations or famil...
Persistent emergence of viral variants capable of evading host immunity constitutes a significant threat to public health. This antigenic evolution fr...
Activity-dependent synaptic plasticity is a fundamental learning mechanism that shapes connectivity and activity of neural circuits. Existing computat...
Continuous glucose monitoring (CGM) systems play a crucial role in diabetes care. Yet, they focus solely on blood glucose levels (BGL), neglect diet, ...
Biomechanical biofeedback has the potential to enhance rehabilitation by providing clinicians with objective evaluation of patient performances. As fe...
Single-cell profiling provides snapshots of the heterogeneous states that characterise developmental processes, organ regeneration and progression tow...
Marked variability in inpatient hospitalization costs poses significant challenges to healthcare quality, resource allocation, and patient outcomes. T...
The critical need for accessible patient data in clinical research is often hindered by privacy regulations and data scarcity. While synthetic data ge...
BACKGROUND: Elder self-neglect (ESN) is usually ignored as a private problem and impairs the health outcomes of older adults. It is essential to const...
MOTIVATION: T-cell receptors (TCRs) elicit and mediate the adaptive immune response by recognizing antigenic peptides, a process pivotal for cancer im...
The in-image machine translation task involves translating text embedded within images, with the translated results presented in image format. While...
Few-shot anomaly detection (FSAD) aims to detect unseen anomaly regions with the guidance of very few normal support images from the same class. Exi...