AIMC Topic: Benchmarking

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On Equivalence of FIS and ELM for Interpretable Rule-Based Knowledge Representation.

IEEE transactions on neural networks and learning systems
This paper presents a fuzzy extreme learning machine (F-ELM) that embeds fuzzy membership functions and rules into the hidden layer of extreme learning machine (ELM). Similar to the concept of ELM that employed the random initialization technique, th...

Deep learning methods for clinical workflow phase-based prediction of procedure duration: a benchmark study.

Computer assisted surgery (Abingdon, England)
This study evaluates the performance of deep learning models in the prediction of the end time of procedures performed in the cardiac catheterization laboratory (cath lab). We employed only the clinical phases derived from video analysis as input to ...

Results of the Protein Engineering Tournament: An Open Science Benchmark for Protein Modeling and Design.

Proteins
The grand challenge of protein engineering is the development of computational models to characterize and generate protein sequences for arbitrary functions. Progress is limited by lack of (1) benchmarking opportunities, (2) large protein function da...

Incorporating respiratory signals for machine learning-based multimodal sleep stage classification: a large-scale benchmark study with actigraphy and heart rate variability.

Sleep
Insufficient sleep quality is directly linked to various diseases, making reliable sleep monitoring crucial for prevention, diagnosis, and treatment. As sleep laboratories are cost- and resource-prohibitive, wearable sensors offer a promising alterna...

3DBench: A scalable benchmark for object and scene-level instruction-tuning of 3D large language models.

Neural networks : the official journal of the International Neural Network Society
Recent assessments of Multi-Modal Large Language Models (MLLMs) have been thorough. However, a detailed benchmark that integrates point cloud data with language for MLLMs remains absent, leading to superficial comparisons that obscure advancements in...

MS25: Materials Science-Focused Benchmark Data Set for Machine Learning Interatomic Potentials.

Journal of chemical information and modeling
We present MS25, a benchmark data set for evaluating machine learning interatomic potentials (MLIPs) across diverse materials-relevant systems including MgO surfaces, liquid water, zeolites, a catalytic Pt surface reaction, high-entropy alloys (HEAs)...

An Electrocardiogram Multi-Task Benchmark with Comprehensive Evaluations and Insightful Findings.

Studies in health technology and informatics
In the process of patient diagnosis, non-invasive measurements are widely used due to their low risks and quick results. Electrocardiogram (ECG), as a non-invasive method to collect heart activities, is used to diagnose cardiac conditions. Analyzing ...

The detection of apical radiolucencies in periapical radiographs: A comparison between an artificial intelligence platform and expert endodontists with CBCT serving as the diagnostic benchmark.

International endodontic journal
AIM: Accurate detection of periapical radiolucent lesions (PARLs) is crucial for endodontic diagnosis. While cone beam computed tomography (CBCT) is considered the radiographic gold standard for detecting PARLs in non-root filled teeth, its use is of...

Assessing Uncertainty in Machine Learning for Polymer Property Prediction: A Benchmark Study.

Journal of chemical information and modeling
Machine learning (ML) has emerged as a transformative tool in material science, enabling accelerated discovery and design of novel molecules while reducing experimental costs. Uncertainty quantification (UQ) is crucial for enhancing the reliability o...

Machine learning models for predicting malnutrition in NICU patients: A comprehensive benchmarking study.

Computers in biology and medicine
Malnutrition, affecting both adults and children globally, results from inadequate nutrient intake or loss of body mass. Traditional screening tools, reliant on detailed questionnaires, are costly, time-consuming, and often lack accuracy and generali...