Latest AI and machine learning research in medical education for healthcare professionals.
This paper proposes an automatic air-to-ground (A2G) channel model selection method based on machine learning (ML) using digital surface model (DSM) terrain data. In order to verify whether a communication network for a new non-terrestrial user service such as Urban Air Mobility (UAM) satisfies the required performance, it is necessary to perform a simulation reflecting the characteristics of the ...
In order to solve the problems of restricted classroom and lack of repeated training in good curriculum, the design and development of a school life adaptation curriculum based on VR is proposed. This study identified six life adaptation themes for design and development (recognizing facial expressions, crossing the road, how to get lost, shopping, taking public transport, and job interview) and s...
Acoustic holography has been gaining attention for various applications, such as noncontact particle manipulation, noninvasive neuromodulation, and me...
Recent developments of heterogeneous advanced oxidation for refractory organic contaminants and catalysts made of solid waste have attracted much atte...
The development of an effective agricultural robot presents various challenges in actuation, localization, navigation, sensing, etc., depending on the...
INTRODUCTION: Practice-Based Learning and Improvement, a core competency identified by the Accreditation Council for Graduate Medical Education, carri...
The use of robotic surgery has increased exponentially in the United States. Despite this uptick in popularity, no standardized training pathway exist...
In this op-ed, we discuss the advantages of leveraging natural language processing (NLP) in the assessment of clinical reasoning. Clinical reasoning i...
OBJECTIVES: Artificial intelligence (AI) is swiftly entering oral health services and dentistry, while most providers show limited knowledge and skill...
With the recent growth of the Internet of Things (IoT) and the demand for faster computation, quantized neural networks (QNNs) or QNN-enabled IoT can ...
BACKGROUND: As the information age wanes, enabling the prevalence of the artificial intelligence age; expectations, responsibilities, and job definiti...
We propose a novel unified frameork for automated distributed active learning (AutoDAL) to address multiple challenging problems in active learning su...
Robotic surgical training is undergoing a period of transition now that new robotic operating platforms are entering clinical practice. As this occurs...
Anatomy is taught in the early years of an undergraduate medical curriculum. The subject is volatile and of voluminous content, given the complex natu...
RATIONALE AND OBJECTIVES: To evaluate the effectiveness of an artificial intelligence (AI) in radiology literacy course on participants from nine radi...
Three-dimensional surgical simulation, already in use for hepatic surgery, can be used in pancreatic surgery. However, some problems still need to be ...
Robotic surgery training has lacked evidence-based standardisation. We aimed to determine the effectiveness of adjunctive interactive virtual classroo...
With the continuous expansion of the Internet in China, network communication models and network services have become more and more complex, and with ...
Hyperdimensional computing (HDC) is a brain-inspired computing paradigm that operates on pseudo-random hypervectors to perform high-accuracy classific...
Artificial intelligence has become ubiquitous with modern technology. Digital transformations are occurring in every field including medicine, surgery...