Latest AI and machine learning research in health policy for healthcare professionals.
This paper focuses on the development of multifidelity modeling approaches using neural network surrogates, where training data arising from multiple model forms and resolutions are integrated to predict high-fidelity response quantities of interest at lower cost. We focus on the context of quantum chemistry and the integration of information from multiple levels of theory. Important foundations i...
The quality of red blood cells (RBCs) in stored blood has a direct impact on the recovery of patients treated by blood transfusion, which directly reflects the quality of blood. The traditional means for blood quality evaluation involve the use of reagents and multi-step and time-consuming operations. Here, a low-cost, multi-classification, label-free and high-precision method is developed, which ...
Potable water, commonly known as drinking water, refers to water that is safe to drink and does not endanger human health. It must adhere to strict qu...
BACKGROUND: Robotic gastrectomy (RG) using the da Vinci Surgical System for gastric cancer was approved for national medical insurance coverage in Jap...
BACKGROUND: Access to oral healthcare is not uniform globally, particularly in rural areas with limited resources, which limits the potential of autom...
The advent of Artificial Intelligence (AI) and the Internet of Things (IoT) have recently created previously unimaginable opportunities for boosting c...
The Sustainable Development Goals (SDGs), also known as the Global Goals, were adopted by the United Nations in 2015 as a universal call to end povert...
Heart failure is a life-threatening syndrome that is diagnosed in 3.6 million people worldwide each year. We propose a deep fusion learning model (DFL...
Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity m...
An otherwise well 28-month-old girl presented with fever/left thigh pain. Computed tomography identified a 7 cm right posterior mediastinal tumor exte...
Modern medicine, both in clinical practice and research, has become more and more based on data, which is changing equally in type and quality with th...
BACKGROUND AND OBJECTIVE: Deep learning is applied in medicine mostly due to its state-of-the-art performance for diagnostic imaging. Supervisory auth...
INTRODUCTION: Artificial intelligence (AI), the simulation of human intelligence processes by machines, is being increasingly leveraged to facilitate ...
Medical device reliability is the ability of medical devices to endure functioning and is indispensable to ensure service delivery to patients. Prefer...
Dementia poses a growing challenge for health services but remains stigmatized and under-recognized. Digital technologies to aid the earlier detection...
BACKGROUND: Robot-assisted total knee arthroplasty (rTKA) may improve clinical outcomes for patients who have end-stage osteoarthritis of the knee. Ho...
In recent years, deep learning models have attracted much attention for classification purposes in chemometrics. The popularity of deep learning model...
The development potential of China's medical insurance market is huge, and the research on medical insurance demand has always been the focus of acade...
Socially assistive devices such as care robots or companions have been advocated as a promising tool in elderly care in Western healthcare systems. Et...
Agricultural productivity can be impaired by poor irrigation water quality. Therefore, adequate vulnerability assessment and identification of the mos...