Latest AI and machine learning research in work force for healthcare professionals.
AI and robotics aim to transform workplace landscapes in a several sectors such as manufacturing, logistics, healthcare, construction, agriculture, and education. Central to this evolution is the innovative use of Digital Twin technology, which creates real-time updated virtual replicas of physical systems and entities. This technology is especially transformative in healthcare and education, prom...
Defining and measuring decision-making styles, also known as playstyles, is crucial in gaming, where these styles reflect a broad spectrum of individuality and diversity. However, finding a universally applicable measure for these styles poses a challenge. Building on Playstyle Distance, the first unsupervised metric to measure playstyle similarity based on game screens and raw actions, we intro...
High-throughput phenotyping automates the mapping of patient signs to standardized ontology concepts and is essential for precision medicine. This s...
BACKGROUND: At present, the number and overall level of ultrasound (US) doctors cannot meet the medical needs, and the medical ultrasound robots will ...
The control strategy of rehabilitation robots should not only adapt to patients with different levels of motor function but also encourage patients to...
The prediction of metabolite-protein interactions (MPIs) plays an important role in plant basic life functions. Compared with the traditional experime...
To construct a robot intelligent discharge follow-up platform and explore its application effects in clinical discharge follow-up scenarios Applying i...
Diversity is a concept of prime importance in almost all disciplines based on information processing. In telecommunications, for example, spatial, t...
Objective. Evaluate the feasibility of Virtual Reality (VR) wayfinding training with aging adults, and examine the impact of the training on wayfind...
The concept of an intelligent augmented reality (AR) assistant has significant, wide-ranging applications, with potential uses in medicine, military...
Machine learning (ML) datasets, often perceived as neutral, inherently encapsulate abstract and disputed social constructs. Dataset curators frequen...
Medical images and radiology reports are crucial for diagnosing medical conditions, highlighting the importance of quantitative analysis for clinica...
Black box deep learning models trained on genomic sequences excel at predicting the outcomes of different gene regulatory mechanisms. Therefore, int...
A number of production deep learning clusters have attempted to explore inference hardware for DNN training, at the off-peak serving hours with many...
Pseudo-labeling based semi-supervised learning (SSL) framework has proven highly successful in medical image analysis (MIA) by addressing the problem ...
Shoulder dislocations are the most common dislocations and there is a demand for a novel traction device for reducing anterior shoulder dislocations, ...
Echocardiography is the only technique capable of real-time imaging of the heart and is vital for diagnosing the majority of cardiac diseases. Howev...
Soft tissue elasticity is directly related to different stages of diseases and can be used for tissue identification during minimally invasive proce...
High-quality Earth Observation (EO) imagery is essential for accurate analysis and informed decision making across sectors. However, data scarcity c...
This vision paper focuses on the mental health crisis impacting healthcare workers (HCWs), which exacerbated by the COVID-19 pandemic, leads to incr...