Staffing & Scheduling

Precise Brain-shift Prediction by New Combination of W-Net Deep Learning for Neurosurgical Navigation.

Brain tissue deformation during surgery significantly reduces the accuracy of image-guided neurosurg...

A Small Step Toward Generalizability: Training a Machine Learning Scoring Function for Structure-Based Virtual Screening.

Over the past few years, many machine learning-based scoring functions for predicting the binding of...

Judging facts, judging norms: Training machine learning models to judge humans requires a modified approach to labeling data.

As governments and industry turn to increased use of automated decision systems, it becomes essentia...

ChatGPT in Medical Education: a Paradigm Shift or a Dangerous Tool?

Show Your Work: Responsible Model Reporting in Health Care Artificial Intelligence.

Standardized and thorough model reporting is an integral component in the development and deployment...

Artificially-generated consolidations and balanced augmentation increase performance of U-net for lung parenchyma segmentation on MR images.

PURPOSE: To improve automated lung segmentation on 2D lung MR images using balanced augmentation and...

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review.

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality g...

A reinforcement learning algorithm acquires demonstration from the training agent by dividing the task space.

Although reinforcement learning (RL) has made numerous breakthroughs in recent years, addressing rew...

Social competence improves the performance of biomimetic robots leading live fish.

Collective motion is commonly modeled with static interaction rules between agents. Substantial empi...

Automation Bias in Mammography: The Impact of Artificial Intelligence BI-RADS Suggestions on Reader Performance.

Background Automation bias (the propensity for humans to favor suggestions from automated decision-m...

Deep Low-Shot Learning for Biological Image Classification and Visualization From Limited Training Samples.

Predictive modeling is useful but very challenging in biological image analysis due to the high cost...

Development of a high fidelity, multidisciplinary, crisis simulation model for robotic surgical teams.

Immediate access to the patient in crisis situations, such as cardiac arrest during robotic surgery,...

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Four-dimensional (4D) data-independent acquisition (DIA)-based proteomics is a promising technology....

Artificial intelligence in surgical education and training: opportunities, challenges, and ethical considerations - correspondence.

Estimating individual minimum calibration for deep-learning with predictive performance recovery: An example case of gait surface classification from wearable sensor gait data.

Clinical datasets often comprise multiple data points or trials sampled from a single participant. W...

Parsable Clinical Trial Eligibility Criteria Representation Using Natural Language Processing.

Successful clinical trials offer better treatments to current or future patients and advance scienti...

Efficacy of Robot-Assisted and Virtual Reality Interventions on Balance, Gait, and Daily Function in Patients With Stroke: A Systematic Review and Network Meta-analysis.

OBJECTIVE: This study aimed to evaluate the comparative effectiveness and ranking of robot-assisted ...

Long term experience of robotic retroperitoneal partial nephrectomy as the default approach in the management of renal masses: should the paradigm shift?

Although retroperitoneal surgery has demonstrated a better quality of recovery compared to transperi...

Gait training with a wearable powered robot during stroke rehabilitation: a randomized parallel-group trial.

BACKGROUND: We have developed a wearable rehabilitation robot, "curara®," and examined its immediate...

Introduction to a Twin Dual-Axis Robotic Platform for Studies of Lower Limb Biomechanics.

This paper presents a twin dual-axis robotic platform system which is designed for the characterizat...

Design of ear-contactless stethoscope and improvement in the performance of deep learning based on CNN to classify the heart sound.

Cardiac-related disorders are rapidly growing throughout the world. Accurate classification of cardi...