Latest AI and machine learning research in practice management for healthcare professionals.
Deep learning-based joint source-channel coding (JSCC) is emerging as a promising technology for effective image transmission. However, most existing approaches focus on transmitting clear images, overlooking real-world challenges such as motion blur caused by camera shaking or fast-moving objects. Motion blur often degrades image quality, making transmission and reconstruction more challenging....
Age prediction using brain imaging, such as MRIs, has achieved promising results, with several studies identifying the model's residual as a potential biomarker for chronic disease states. In this study, we developed a brain age predictive model using a dataset of 1,220 U.S. veterans (18--80 years) and convolutional neural networks (CNNs) trained on two-dimensional slices of axial T2-weighted fa...
The image compression model has long struggled with adaptability and generalization, as the decoded bitstream typically serves only human or machine...
Coping with the impact of dynamic channels is a critical issue in joint source-channel coding (JSCC)-based semantic communication systems. In this p...
Joint source-channel coding (JSCC) is a promising paradigm for next-generation communication systems, particularly in challenging transmission envir...
Cloud gaming is an advanced form of Internet service that necessitates local terminals to decode within limited resources and time latency. Super-Re...
Making good decisions is essential for survival and success, yet humans and animals often exhibit perplexing irrational decision-making whose biologic...
To explore multiomic regulation of the metabolome, we used machine learning to predict metabolomic variation across ∼1000 different cancer cell lines ...
Estrogen receptor alpha (ERα)-positive (ER+) breast cancers are driven by 17β-estradiol (E2) binding to ERα, which transcriptionally regulates downstr...
Life unfolds continuously across multiple timescales, yet how the brain encodes hierarchical event sequences remains poorly understood. Using magnetoe...
Understanding how the human brain decodes facial expressions remains a fundamental challenge, requiring computational models that tightly connect neur...
The brain navigates complex environments by combining entorhinal grid codes with hippocampal place codes. Although grid codes effectively represent a ...
Mitochondria in Plasmodium vivax are functionally vital despite possessing a highly reduced genome and differing substantially from the human organell...
The brain seamlessly transforms sensory information into precisely-timed movements, enabling us to type familiar words, play musical instruments, or p...
Genomic language models (gLMs) have emerged as a powerful approach for learning genome-wide functional constraints directly from DNA sequences. Howeve...
The primate visual system is a hierarchical network of brain areas that transform retinal inputs into rich percepts. According to efficient neural cod...
The hippocampal–entorhinal system supports spatial navigation and memory by orchestrating the interaction between grid cells and place cells. While va...
Emotional expression in dogs is central to dog-human interactions. Reliable indicators are essential for interpreting animal emotions; however, their ...
A challenge in sensory neuroscience is understanding how populations of neurons operate in concert to represent diverse stimuli. To meet this challeng...
Cortical circuits produce time-varying patterns of population and single neuron activity that play a fundamental role in perceptual and behavioral pro...