AIMC Topic: Benchmarking

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Proficiency-based progression training for robotic surgery skills training: a randomized clinical trial.

BJU international
OBJECTIVE: To determine whether proficiency-based progression (PBP) training leads to better robotic surgical performance compared to traditional training (TT), given that the value of PBP training for learning robotic surgical skills is unclear.

Benchmarking Deep Learning Models for Tooth Structure Segmentation.

Journal of dental research
A wide range of deep learning (DL) architectures with varying depths are available, with developers usually choosing one or a few of them for their specific task in a nonsystematic way. Benchmarking (i.e., the systematic comparison of state-of-the ar...

Decisions are not all equal-Introducing a utility metric based on case-wise raters' perceptions.

Computer methods and programs in biomedicine
Background and Objective Evaluation of AI-based decision support systems (AI-DSS) is of critical importance in practical applications, nonetheless common evaluation metrics fail to properly consider relevant and contextual information. In this articl...

Artificial Intelligence Methods and Artificial Intelligence-Enabled Metrics for Surgical Education: A Multidisciplinary Consensus.

Journal of the American College of Surgeons
BACKGROUND: Artificial intelligence (AI) methods and AI-enabled metrics hold tremendous potential to advance surgical education. Our objective was to generate consensus guidance on specific needs for AI methods and AI-enabled metrics for surgical edu...

DeepNC: a framework for drug-target interaction prediction with graph neural networks.

PeerJ
The exploration of drug-target interactions (DTI) is an essential stage in the drug development pipeline. Thanks to the assistance of computational models, notably in the deep learning approach, scientists have been able to shorten the time spent on ...

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology.

Medical image analysis
Artificial intelligence (AI) can extract visual information from histopathological slides and yield biological insight and clinical biomarkers. Whole slide images are cut into thousands of tiles and classification problems are often weakly-supervised...

Swarm of micro flying robots in the wild.

Science robotics
Aerial robots are widely deployed, but highly cluttered environments such as dense forests remain inaccessible to drones and even more so to swarms of drones. In these scenarios, previously unknown surroundings and narrow corridors combined with requ...

Monitoring Approaches for a Pediatric Chronic Kidney Disease Machine Learning Model.

Applied clinical informatics
OBJECTIVE: The purpose of this study is to evaluate the ability of three metrics to monitor for a reduction in performance of a chronic kidney disease (CKD) model deployed at a pediatric hospital.

Interpretability and fairness evaluation of deep learning models on MIMIC-IV dataset.

Scientific reports
The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications. However, due to the nature of such deep black-boxed models, concerns about interpretability, fai...

An efficient rotational direction heap-based optimization with orthogonal structure for medical diagnosis.

Computers in biology and medicine
The heap-based optimizer (HBO) is an optimization method proposed in recent years that may face local stagnation problems and show slow convergence speed due to the lack of detailed analysis of optimal solutions and a comprehensive search. Therefore,...