Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
The inverse relationship between the cost of drug development and the successful integration of drugs into the market has resulted in the need for innovative solutions to overcome this burgeoning problem. This problem could be attributed to several factors, including the premature termination of clinical trials, regulatory factors, or decisions made in the earlier drug development processes. The i...
Pedestrian detection through Computer Vision is a building block for a multitude of applications. Recently, there has been an increasing interest in convolutional neural network-based architectures to execute such a task. One of these supervised networks' critical goals is to generalize the knowledge learned during the training phase to new scenarios with different characteristics. A suitably labe...
Local trauma care and regional trauma systems are data-rich environments that are amenable to machine learning, artificial intelligence, and big-data ...
When making an appointment, patients are generally unaware of how much clinician time is available to address their concerns. Similarly, the primary c...
Lower-limb wearable robotic devices can improve clinical gait and reduce energetic demand in healthy populations. To help enable real-world use, we so...
Artificial intelligence (AI) employs knowledge models that often behave as a black-box to the majority of users and are not designed to improve the s...
BACKGROUND: This study prospectively assessed the diagnostic capacity of dynamic carbon-11 methionine (C-11 MET) positron-emission tomography (PET)/co...
Artificial intelligence (AI) will transform every step in the imaging value chain, including interpretive and noninterpretive components. Radiologists...
Deep Learning (DL) algorithms are a set of techniques that exploit large and/or complex real-world datasets for cross-domain and cross-discipline pred...
BACKGROUND: Body weight support systems with three or more degrees of freedom (3-DoF) are permissive and safe environments that provide unloading and ...
The main objective of this paper is to present a systematic analysis and review of the state of the art regarding the prediction of absenteeism and te...
Accurate segmentation of brain magnetic resonance imaging (MRI) is an essential step in quantifying the changes in brain structure. Deep learning in r...
Since the launch of Chinese Human Proteome Project (CNHPP) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), large-scale mass spectrometry (MS...
BACKGROUND AND OBJECTIVE: Peripherally inserted central catheter (PICC) is a novel drug delivery mode which has been widely used in clinical practice....
This research aims to analyze the effects of different parameter estimation on the recognition performance of satellite modulation signals based on de...
In this paper, the protocol-based remote state estimation problem is considered for a kind of delayed artificial neural networks. The random time-vary...
A rapid GC-FID method was developed to simultaneously determine residual levels of triethylamine (TEA), 1,1,3,3-tetramethylguanidine (TMG), and diisop...
Gyroscopic actuators are appealing for wearable applications due to their ability to provide overground balance support without obstructing the legs. ...
We propose a novel active learning framework for activity recognition using wearable sensors. Our work is unique in that it takes limitations of the o...
Maintaining a fair use of energy consumption in smart homes with many household appliances requires sophisticated algorithms working together in real ...