AIMC Topic: Benchmarking

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Predicting Surgical Experience After Robotic Nerve-sparing Radical Prostatectomy Simulation Using a Machine Learning-based Multimodal Analysis of Objective Performance Metrics.

Urology practice
INTRODUCTION: Machine learning methods have emerged as objective tools to evaluate operative performance in urological procedures. Our objectives were to establish machine learning-based methods for predicting surgeon caseload for nerve-sparing robot...

Underwater Target Detection Utilizing Polarization Image Fusion Algorithm Based on Unsupervised Learning and Attention Mechanism.

Sensors (Basel, Switzerland)
Since light propagation in water bodies is subject to absorption and scattering effects, underwater images using only conventional intensity cameras will suffer from low brightness, blurred images, and loss of details. In this paper, a deep fusion ne...

NR5G-SAM: A SLAM Framework for Field Robot Applications Based on 5G New Radio.

Sensors (Basel, Switzerland)
Robot localization is a crucial task in robotic systems and is a pre-requisite for navigation. In outdoor environments, Global Navigation Satellite Systems (GNSS) have aided towards this direction, alongside laser and visual sensing. Despite their ap...

Synthetic Patient Data Generation and Evaluation in Disease Prediction Using Small and Imbalanced Datasets.

IEEE journal of biomedical and health informatics
The increasing prevalence of chronic non-communicable diseases makes it a priority to develop tools for enhancing their management. On this matter, Artificial Intelligence algorithms have proven to be successful in early diagnosis, prediction and ana...

Issue of Data Imbalance on Low Birthweight Baby Outcomes Prediction and Associated Risk Factors Identification: Establishment of Benchmarking Key Machine Learning Models With Data Rebalancing Strategies.

Journal of medical Internet research
BACKGROUND: Low birthweight (LBW) is a leading cause of neonatal mortality in the United States and a major causative factor of adverse health effects in newborns. Identifying high-risk patients early in prenatal care is crucial to preventing adverse...

Characteristics and Emerging Trends in Research on Rehabilitation Robots from 2001 to 2020: Bibliometric Study.

Journal of medical Internet research
BACKGROUND: The past 2 decades have seen rapid development in the use of robots for rehabilitation. Research on rehabilitation robots involves interdisciplinary activities, making it a great challenge to obtain comprehensive insights in this research...

Comparison of evaluation metrics of deep learning for imbalanced imaging data in osteoarthritis studies.

Osteoarthritis and cartilage
PURPOSE: To compare the evaluation metrics for deep learning methods that were developed using imbalanced imaging data in osteoarthritis studies.

An annotated human blastocyst dataset to benchmark deep learning architectures for in vitro fertilization.

Scientific data
Medical Assisted Reproduction proved its efficacy to treat the vast majority forms of infertility. One of the key procedures in this treatment is the selection and transfer of the embryo with the highest developmental potential. To assess this potent...

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

The Surgical clinics of North America
Standardized and thorough model reporting is an integral component in the development and deployment of machine learning models in health care. Model reporting includes sharing multiple model performance metrics and incorporating metadata to provide ...

JRDB: A Dataset and Benchmark of Egocentric Robot Visual Perception of Humans in Built Environments.

IEEE transactions on pattern analysis and machine intelligence
We present JRDB, a novel egocentric dataset collected from our social mobile manipulator JackRabbot. The dataset includes 64 minutes of annotated multimodal sensor data including stereo cylindrical 360 RGB video at 15 fps, 3D point clouds from two 1...