This commentary on a case considers balancing prospective benefits and harms of robotic technology use and argues that health care organizations should invest in centralizing robotic expertise in departments rather than having a mere collection of su...
INTRODUCTION: We estimate the economic impact of applying risk assessment tools to identify very low-risk patients with upper gastrointestinal bleeding who can be safely discharged from the emergency department using a cost minimization analysis.
Journal of the American College of Radiology : JACR
38072221
Radiology is on the verge of a technological revolution driven by artificial intelligence (including large language models), which requires robust computing and storage capabilities, often beyond the capacity of current non-cloud-based informatics sy...
INTRODUCTION: Most patients suffering from neurological disorders endure varying degrees of upper limb dysfunction, limiting their everyday activities, with only a limited number regaining full arm use. Robotic and technological rehabilitation has be...
Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation
38384228
OBJECTIVE: Medical consumables are expensive, with numerous specifications and large usage, and traditional manual management models have certain drawbacks. Building an intelligent logistics management system to improve management level.
The surgical robot is assumed to be a fixed, indirect cost. We hypothesized rising volume of robotic bariatric procedures would decrease cost per patient over time. Patients who underwent elective, initial gastric bypass (GB) or sleeve gastrectomy (S...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
39191190
PURPOSE: To evaluate a deep learning model's performance in predicting and classifying patient-specific quality assurance (PSQA) results for volumetric modulated arc therapy (VMAT), aiming to streamline PSQA workflows and reduce the onsite measuremen...
In view of the shortcomings of power engineering cost in precision and dynamic in big data environments, this paper proposes building information modelling (BIM) and spatiotemporal modelling-based dynamic graph convolutional neural networks (DynGCN)....
This study compares the precision and interpretability of two automated valuation models for evaluating the real estate market in the Santiago Metropolitan Region of Chile: machine learning algorithms, specifically LightGBM, and hedonic prices with s...
The rapid evolution of large language models (LLMs) and machine learning (ML) presents both significant opportunities and challenges for market access processes. These sophisticated AI systems, built on transformer architectures and extensive dataset...