Work Force

The value of standards for health datasets in artificial intelligence-based applications.

Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in res...

Analysis of learning the bimanual control of (tele)operating joint space controlled robotic arms with 4 degrees of freedom using the two-timescales power law of learning.

Training costs for operators of robotic arms in forestry and construction are high. A systematic analysis of skill development can help to make training more efficient. This research focuses on motor skill development by investigating the bimanual control of a four-DoF robotic arm. The two-time scale power law of learning was used to identify difficulties in control learning. Ten participants acqu...

From an Empty, to an Almost Full, and Eventually to a Never Full Glass: The Evolving Challenges of Medical Education.

It has traditionally been considered that the larger the amount of knowledge, the greater the competency of a physician. However, the vertiginously fa...

Deep learning with citizen science data enables estimation of species diversity and composition at continental extents.

Effective solutions to conserve biodiversity require accurate community- and species-level information at relevant, actionable scales and across entir...

Using natural language processing to increase prediction and reduce subgroup differences in personnel selection decisions.

The purpose of this research is to demonstrate how using natural language processing (NLP) on narrative application data can improve prediction and re...

Applying an artificial intelligence deep learning approach to routine dermatopathological diagnosis of basal cell carcinoma.

BACKGROUND: Institutes of dermatopathology are faced with considerable challenges including a continuously rising numbers of submitted specimens and a...

Artificial intelligence in diabetes management: Advancements, opportunities, and challenges.

The increasing prevalence of diabetes, high avoidable morbidity and mortality due to diabetes and diabetic complications, and related substantial econ...

Addressing the challenges of AI-based telemedicine: Best practices and lessons learned.

Telemedicine is the use of technology to provide healthcare services and information remotely, without requiring physical proximity between patients a...

Selecting cardiac magnetic resonance images suitable for annotation of pulmonary arteries using an active-learning based deep learning model.

An increasing and aging patient population poses a growing burden on healthcare professionals. Automation of medical imaging diagnostics holds promise...

New deep learning-based methods for visualizing ecosystem properties using environmental DNA metabarcoding data.

Environmental DNA (eDNA) metabarcoding provides an efficient approach for documenting biodiversity patterns in marine and terrestrial ecosystems. The ...

Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation.

The role of fibrillar collagen in the tissue microenvironment is critical in disease contexts ranging from cancers to chronic inflammations, as eviden...

Adv-BDPM: Adversarial attack based on Boundary Diffusion Probability Model.

Deep neural networks have become increasingly significant in our daily lives due to their remarkable performance. The issue of adversarial examples, w...

SCANet: A Unified Semi-Supervised Learning Framework for Vessel Segmentation.

Automatic subcutaneous vessel imaging with near-infrared (NIR) optical apparatus can promote the accuracy of locating blood vessels, thus significantl...

Investigation with able-bodied subjects suggests Myosuit may potentially serve as a stair ascent training robot.

Real world settings are seldomly just composed of level surfaces and stairs are frequently encountered in daily life. Unfortunately, ~ 90% of the elde...

Human Factors Considerations for Quantifiable Human States in Physical Human-Robot Interaction: A Literature Review.

As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older...

Robotic Medtronic Hugo™ RAS System Is Now Reality: Introduction to a New Simulation Platform for Training Residents.

The use of robotic surgery (RS) in urology has grown exponentially in the last decade, but RS training has lagged behind. The launch of new robotic pl...

Machine learning-based radiotherapy time prediction and treatment scheduling management.

PURPOSE: The utility efficiency of medical devices is important, especially for countries such as China, which have a large population and shortage of...

Spatial oblivion channel attention targeting intra-class diversity feature learning.

Convolutional neural networks (CNNs) have successfully driven many visual recognition tasks including image classification. However, when dealing with...

Customized Trajectory Optimization and Compliant Tracking Control for Passive Upper Limb Rehabilitation.

Passive rehabilitation training in the early poststroke period can promote the reshaping of the nervous system. The trajectory should integrate the ph...

Toward a stable and low-resource PLM-based medical diagnostic system via prompt tuning and MoE structure.

Machine learning (ML) has been extensively involved in assistant disease diagnosis and prediction systems to emancipate the serious dependence on medi...