The efficacy of deep residual networks is fundamentally predicated on the identity shortcut connection. While this mechanism effectively mitigates the vanishing gradient problem, it imposes a strictly ...

A NEWLY published retrospective study has shown that AI, particularly deep-learning algorithms, can significantly reduce the rate of misdiagnosis in paediatric elbow fractures. The study analysed 755 ...

A total of 17.9 million people were estimated to be living with rheumatoid arthritis globally in 2021, representing a 13.2% increase in incidence since 1990. The global burden of rheumatoid arthritis ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...

Almost a full year into President Donald Trump‘s second term, the full scope of the federal government’s woke and weaponized posture toward its citizens is still unfolding. Beyond the known targeting ...

aDepartment of Medical Ultrasonics, Affiliated Shenzhen Children's Hospital, College of Medicine, Shantou University, No. 7019 Yitian Road, Shenzhen, China bShenzhen University Medical School, ...

What the deep state does well is to use the bureaucracy’s failings and inefficiencies to cover its tracks. Transparency and accountability can get lost in clerical processes. Ambiguous official ...

A new machine learning model developed by The George Institute for Global Health can successfully predict heart disease risk in women by analyzing mammograms. The findings were published today in ...

Abstract: The success of deep learning (DL) is often achieved at the expense of large model sizes and high computational complexity during both training and post-training inferences, making it ...

Abstract: Recent advancements in deep neural networks heavily rely on large-scale labeled datasets. However, acquiring annotations for large datasets can be challenging due to annotation constraints.