Latest AI and machine learning research in medicare for healthcare professionals.
Long-tailed classification is challenging due to its heavy imbalance in class probabilities. While existing methods often focus on overall accuracy or accuracy for tail classes, they overlook a critical aspect: certain types of errors can carry greater risks than others in real-world long-tailed problems. For example, misclassifying patients (a tail class) as healthy individuals (a head class) e...
The interconnection between the human lungs and other organs, such as the liver and kidneys, is crucial for understanding the underlying risks and effects of lung diseases and improving patient care. However, most research chest CT imaging is focused solely on the lungs due to considerations of cost and radiation dose. This restricted field of view (FOV) in the acquired images poses challenges t...
Object-centric slot attention is a powerful framework for unsupervised learning of structured and explainable representations that can support reaso...
Depth Anything has achieved remarkable success in monocular depth estimation with strong generalization ability. However, it suffers from temporal i...
Personalized speech enhancement (PSE) methods typically rely on pre-trained speaker verification models or self-designed speaker encoders to extract...
Genome-centric analysis of metagenomic samples is a powerful method for understanding the function of microbial communities. Calculating read covera...
Standard conformal prediction offers a marginal guarantee on coverage, but for prediction sets to be truly useful, they should ideally ensure covera...
Target Speech Extraction (TSE) traditionally relies on explicit clues about the speaker's identity like enrollment audio, face images, or videos, wh...
The field of brainwave-based biometrics has gained attention for its potential to revolutionize user authentication through hands-free interaction, ...
Many real-world systems can be modeled as dynamic graphs, where nodes and edges evolve over time, requiring specialized models to capture their evol...
Fair operational systems are crucial in gaining and maintaining society's trust in face recognition systems (FRS). FRS start with capturing an image...
Recent video generation models have shown promising results in producing high-quality video clips lasting several seconds. However, these models fac...
We demonstrate how dynamic verification (e.g. simulation) can be replaced by deductive formal verification and how to benefit from the advantages of...
Understanding communication and information processing among brain regions of interest (ROIs) is highly dependent on long-range connectivity, which ...
Fragmentomics of plasma cell-free DNA (cfDNA) are emerging diagnostic biomarkers in cancer liquid biopsy, while the molecular regulations of cfDNA fra...
The relation between regional morphological features derived from the bilaterian body plan and the behaviours necessary to extract utility from such s...
Identifying effector proteins of Gram-negative bacterial secretion systems is crucial for understanding their pathogenic mechanisms and guiding antimi...
Fertility is one of the major factors affecting the efficiency of dairy herd, and genomic selection (GS) on milk yield, while ignoring fertility, has ...
The development of highly accurate protein structure prediction algorithms has led to an explosion of structural data, transforming our understanding ...
Extracellular vesicles (EVs), including exosomes, are emerging as promising carriers of disease-specific biomarkers due to their molecular cargo refle...