Physical AI connects algorithms to the real world. Learn how embodied systems sense, adapt, and operate beyond pure computation.
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
Abstract: Future 6G Integrated Sensing and Communication (ISAC) networks are expected to reuse data payload signals for both communication and sensing. However, the inherent randomness of these ...
Background Gut microbiota dysbiosis is linked to autism spectrum disorder (ASD) in children. However, the role of bacterial ...
Optokinetic Nystagmus (OKN) is a natural reflexive eye movement in oculomotor studies, reflecting the health status of the visual system. Through accurate eye center annotation, physicians can observe ...
Abstract: An incremental iterative Q-learning algorithm (IIQLA) is proposed to tackle the optimal secure control problem for cyber-physical systems under false data injection attacks. Within a ...
Introduction Perinatal depression poses substantial risks to both mothers and their offspring. Given its chronic and ...
Machine learning systems embed preferences either in training losses or through post-processing of calibrated predictions. Applying information design methods from Strack and Yang (2024), this paper ...
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