Staffing & Scheduling

Digital twin rehabilitation system based on self-balancing lower limb exoskeleton.

BACKGROUND: The digital twin concept is the virtual model based on entity design measures, which is used in many enterprises' virtual workshop design models for workshop production scheduling and optimization. However, in the field of medical rehabilitation, the integration of digital twin technology started late compared to traditional industrial manufacturing. Many current digital models are not...

A Machine Learning-Based Initial Difficulty Level Adjustment Method for Balance Exercise on a Trunk Rehabilitation Robot.

Trunk rehabilitation exercises such as those for remediating core stability can help improve the seated balance of patients with weakness or loss of proprioception caused by diseases such as stroke, and aid the recovery of other functions such as gait. However, there has not yet been any reported method for automatically determining the parameters that define exercise difficulty on a trunk rehabil...

Natural History and Real-World Data in Rare Diseases: Applications, Limitations, and Future Perspectives.

Rare diseases represent a highly heterogeneous group of disorders with high phenotypic and genotypic diversity within individual conditions. Due to th...

[Application of robot-assisted laparoscopic sentinel lymph node tracing in treating endometrial carcinoma].

To investigate the value of robot-assisted laparoscopic indocyanine green sentinel lymph node (SLN) tracing in treating endometrial carcinoma. Thirt...

Multi-model fusion short-term power load forecasting based on improved WOA optimization.

The high accuracy of short-term power load forecasting has a pivotal role in helping power companies to construct reasonable production scheduling pla...

Physics-informed neural networks based on adaptive weighted loss functions for Hamilton-Jacobi equations.

Physics-informed neural networks (PINN) have lately become a research hotspot in the interdisciplinary field of machine learning and computational mat...

Information Geometrically Generalized Covariate Shift Adaptation.

Many machine learning methods assume that the training and test data follow the same distribution. However, in the real world, this assumption is ofte...

DeepSCP: utilizing deep learning to boost single-cell proteome coverage.

Multiplexed single-cell proteomes (SCPs) quantification by mass spectrometry greatly improves the SCP coverage. However, it still suffers from a low n...

Human balance augmentation via a supernumerary robotic tail.

Humans are intrinsically unstable in quiet stance from a rigid body system viewpoint; however, they maintain balance thanks to neuro-muscular sensory ...

Accurate Continuous Prediction of 14 Degrees of Freedom of the Hand from Myoelectrical Signals through Convolutive Deep Learning.

Natural control of assistive devices requires continuous positional encoding and decoding of the user's volition. Human movement is encoded by recruit...

Extravasation Screening and Severity Prediction from Skin Lesion Image using Deep Neural Networks.

Extravasation occurs secondary to the leakage of medication from blood vessels into the surrounding tissue during intravenous administration resulting...

Hospital-Agnostic Image Representation Learning in Digital Pathology.

Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference in procedures to acquire WSIs at various trial sit...

Redistributing Ground Reaction Forces During Squatting Using a Cable-Driven Robotic Device.

Squatting is a dynamic task that is often done for strengthening and improving balance. Most squat training systems partially support body weight. How...

Improving Ankle Muscle Recruitment via Plantar Pressure Biofeedback during Robot Resisted Gait Training in Cerebral Palsy.

Neurological impairment from stroke or cerebral palsy often presents with diminished ankle plantar flexor function during the propulsive phase of gait...

Learning Dynamic Patient-Robot Task Assignment and Scheduling for A Robotic Rehabilitation Gym.

A robotic rehabilitation gym is a setup that allows multiple patients to exercise together using multiple robots. The effectiveness of training in suc...

A Machine Learning Solution to Predict Elective Orthopedic Surgery Case Duration.

We used surgery durations, patient demographic and personnel data taken from the East Kent Hospitals University NHS Foundation Trust (EKHUFT) over a p...

Optical random micro-phase-shift DropConnect in a diffractive deep neural network.

The formulation and training of unitary neural networks is the basis of an active modulation diffractive deep neural network. In this Letter, an optic...

The Role of the Robotics Coordinator: Improving Efficiency in a Robotic Surgery Program.

An increase in the number of surgical robots from four to nine at a large academic medical center in the northeastern United States created several ch...

Decision support model for the patient admission scheduling problem based on picture fuzzy aggregation information and TOPSIS methodology.

Health care systems around the world do not have sufficient medical services to immediately offer elective (e.g., scheduled or non-emergency) services...

Artificial Intelligence and Positron Emission Tomography Imaging Workflow:: Technologists' Perspective.

Artificial intelligence (AI) can enhance the efficiency of medical imaging quality control and clinical documentation, provide clinical decision suppo...