Latest AI and machine learning research in surveys for healthcare professionals.
Human segmentation and tracking often use the outcome of person detection in the video. Thus, the results of segmentation and tracking depend heavily on human detection results in the video. With the advent of Convolutional Neural Networks (CNNs), there are excellent results in this field. Segmentation and tracking of the person in the video have significant applications in monitoring and estimati...
INTRODUCTION: Drowsiness is one of the main contributors to road-related crashes and fatalities worldwide. To address this pressing global issue, researchers are continuing to develop driver drowsiness detection systems that use a variety of measures. However, most research on drowsiness detection uses approaches based on a singular metric and, as a result, fail to attain satisfactory reliability ...
This study proposes a new index to measure the resilience of an individual to stress, based on the changes of specific physiological variables. These ...
Artificial intelligence (AI) systems have increasingly achieved expert-level performance in medical imaging applications. However, there is growing co...
OBJECTIVE: The objectives of this scoping review are to identify the reliability and validity of the available tools, their limitations and any recomm...
This paper is a continuation of research into the possibility of using fuzzy logic to assess the reliability of a selected airborne system. The resear...
Population and public health are in the midst of an artificial intelligence revolution capable of radically altering existing models of care delivery ...
Subarachnoid hemorrhage (SAH) is one of the critical and severe neurological diseases with high morbidity and mortality. Head computed tomography (CT)...
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mech...
In this paper, we analyzed the application value and effect of deep learn-based image segmentation model of convolutional neural network (CNN) algorit...
We sought to apply natural language processing to the task of automatic risk of bias assessment in preclinical literature, which could speed the proce...
BACKGROUND: The Cox proportional hazards model with neural networks is widely used to accurately predict survival outcome for choosing cancer treatmen...
In this article, we study activity recognition in the context of sensor-rich environments. In these environments, many different constraints arise at ...
Predicting the travel demand plays an indispensable role in urban transportation planning. Data collection methods for estimating the origin-destinati...
Many metrics such as accuracy rate (ACC), area under curve (AUC), Jaccard index (JI), and Cohen's kappa coefficient are available to measure the succe...
Healthy aging is a new challenge for the world. Therefore, health literacy education is a key issue in the current health care field. This research ha...
Due to the non-uniformity of bond stress distribution, the full bar development length should be tested to validate the development length of the rein...
Cognitive performance can be predicted from an individual's functional brain connectivity with modest accuracy using machine learning approaches. As y...
Various intelligent technologies have been applied during COVID-19, which has become a worldwide public health emergency and brought significant chall...
The present study seeks to examine individuals' stream of thought in real time. Specifically, we asked participants to speak their thoughts freely out...