Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Research on a terrain-blind walking control that can walk stably on unknown and uneven terrain is an important research field for humanoid robots to achieve human-level walking abilities, and it is still a field that needs much improvement. This paper describes the design, implementation, and experimental results of a robust balance-control framework for the stable walking of a humanoid robot on u...
Deep learning has been used to analyze and diagnose various skin diseases through medical imaging. However, recent researches show that a well-trained deep learning model may not generalize well to data from different cohorts due to domain shift. Simple data fusion techniques such as combining disease samples from different data sources are not effective to solve this problem. In this paper, we pr...
The future implications of climate change on malaria transmission at the global level have already been reported, however such evidences are scarce an...
: The Gait Exercise Assist Robot (GEAR) has been developed to support gait training for stroke patients. The GEAR can assist paretic lower limb swing ...
A thorough understanding of anterior cruciate ligament (ACL) function and the effects of surgical interventions on knee biomechanics requires robust t...
We present ChromAlignNet, a deep learning model for alignment of peaks in Gas Chromatography-Mass Spectrometry (GC-MS) data. In GC-MS data, a compound...
BACKGROUND: Intensive care units (ICUs) face financial, bed management, and staffing constraints. Detailed data covering all aspects of patients' jour...
One of the most challenging tasks in modern science is the development of systems biology models: Existing models are often very complex but generally...
A deep convolutional neural network was used for the estimation of gas chromatographic retention indices on non-polar (polydimethylsiloxane and polydi...
BACKGROUND: Balance impairments are common in patients with infratentorial stroke. Although robot-assisted gait training (RAGT) exerts positive effect...
A neural network model was previously developed to predict melatonin rhythms accurately from blue light and skin temperature recordings in individuals...
The aim of this paper is to reverse an assembly line, to be able to perform disassembly, using two complex autonomous systems (CASs). The disassembly ...
Behavior is controlled by complex neural networks in which neurons process thousands of inputs. However, even short spike trains evoked in a single co...
We used two simple unsupervised machine learning techniques to identify differential trajectories of change in children who undergo intensive working ...
Untethered small-scale robots have great potential for biomedical applications. However, critical barriers to effective translation of these miniaturi...
BACKGROUND: Accurate estimation of operative case-time duration is critical for optimizing operating room use. Current estimates are inaccurate and ea...
In this paper, a hybrid deep neural network scheduler (HDNNS) is proposed to solve job-shop scheduling problems (JSSPs). In order to mine the state in...
Different adaptation rates have been reported in studies involving ankle exoskeletons designed to reduce the metabolic cost of their wearers. This wor...
OBJECTIVES: To provide proof-of-concept for a protocol applying a strategy of personalized mechanical ventilation in children with acute respiratory d...
Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the biological significance of functional single-nucleoti...