AIMC Topic: Benchmarking

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Intelligent checklists improve checklist compliance in the intensive care unit: a prospective before-and-after mixed-method study.

British journal of anaesthesia Nov 17, 2020
BACKGROUND: We examined whether a context and process-sensitive 'intelligent' checklist increases compliance with best practice compared with a paper checklist during intensive care ward rounds.
Benchmarking Critical Care Quality Improvement Guideline Adherence Artificial Intelligence Health Status Patient Safety Paper Prospective Studies Practice Patterns, Physicians' Intensive Care Units Attitude to Computers Length of Stay Humans Teaching Rounds Decision Support Systems, Clinical Quality Indicators, Health Care Practice Guidelines as Topic Checklist
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Machine Learning and Improved Quality Metrics in Acute Intracranial Hemorrhage by Noncontrast Computed Tomography.

Current problems in diagnostic radiology Nov 15, 2020
OBJECTIVE: The timely reporting of critical results in radiology is paramount to improved patient outcomes. Artificial intelligence has the ability to improve quality by optimizing clinical radiology workflows. We sought to determine the impact of a ...
Humans Artificial Intelligence Machine Learning Benchmarking Retrospective Studies Intracranial Hemorrhages Tomography, X-Ray Computed Emergency Service, Hospital
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Federated Learning on Clinical Benchmark Data: Performance Assessment.

Journal of medical Internet research Oct 26, 2020
BACKGROUND: Federated learning (FL) is a newly proposed machine-learning method that uses a decentralized dataset. Since data transfer is not necessary for the learning process in FL, there is a significant advantage in protecting personal privacy. T...
Reproducibility of Results Benchmarking Humans Machine Learning Learning
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Correntropy induced loss based sparse robust graph regularized extreme learning machine for cancer classification.

BMC bioinformatics Oct 7, 2020
BACKGROUND: As a machine learning method with high performance and excellent generalization ability, extreme learning machine (ELM) is gaining popularity in various studies. Various ELM-based methods for different fields have been proposed. However, ...
Computational Biology Benchmarking Humans Machine Learning Databases, Factual Neoplasms
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LncLocation: Efficient Subcellular Location Prediction of Long Non-Coding RNA-Based Multi-Source Heterogeneous Feature Fusion.

International journal of molecular sciences Oct 1, 2020
Recent studies uncover that subcellular location of long non-coding RNAs (lncRNAs) can provide significant information on its function. Due to the lack of experimental data, the number of lncRNAs is very limited, experimentally verified subcellular l...
Base Sequence Genome, Human Terminology as Topic Datasets as Topic Cell Nucleus Gene Expression Regulation Cytoplasm Ribosomes Eukaryotic Cells Computational Biology Support Vector Machine Databases, Genetic RNA, Long Noncoding Benchmarking Exosomes Humans Software Animals
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Deep Learning-based Noise Reduction for Fast Volume Diffusion Tensor Imaging: Assessing the Noise Reduction Effect and Reliability of Diffusion Metrics.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Sep 18, 2020
To assess the feasibility of a denoising approach with deep learning-based reconstruction (dDLR) for fast volume simultaneous multi-slice diffusion tensor imaging of the brain, noise reduction effects and the reliability of diffusion metrics were eva...
Anisotropy Reproducibility of Results Deep Learning Benchmarking Image Processing, Computer-Assisted Diffusion Tensor Imaging Humans
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Integrative Benchmarking to Advance Neurally Mechanistic Models of Human Intelligence.

Neuron Sep 11, 2020
A potentially organizing goal of the brain and cognitive sciences is to accurately explain domains of human intelligence as executable, neurally mechanistic models. Years of research have led to models that capture experimental results in individual ...
Brain Models, Neurological Intelligence Benchmarking Humans Neural Networks, Computer
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As if sand were stone. New concepts and metrics to probe the ground on which to build trustable AI.

BMC medical informatics and decision making Sep 11, 2020
BACKGROUND: We focus on the importance of interpreting the quality of the labeling used as the input of predictive models to understand the reliability of their output in support of human decision-making, especially in critical domains, such as medic...
Humans Artificial Intelligence Algorithms Reproducibility of Results Benchmarking
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cnnAlpha: Protein disordered regions prediction by reduced amino acid alphabets and convolutional neural networks.

Proteins Aug 7, 2020
Intrinsically disordered regions (IDR) play an important role in key biological processes and are closely related to human diseases. IDRs have great potential to serve as targets for drug discovery, most notably in disordered binding regions. Accurat...
Data Mining Datasets as Topic Intrinsically Disordered Proteins Humans Area Under Curve Neural Networks, Computer Benchmarking Amino Acid Sequence Machine Learning ROC Curve Computational Biology Sequence Analysis, Protein Multifactor Dimensionality Reduction
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Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology.

JMIR mHealth and uHealth Jul 31, 2020
BACKGROUND: There has been a recent increased interest in monitoring health using wearable sensor technologies; however, few have focused on breathing. The ability to monitor breathing metrics may have indications both for general health as well as r...
Respiratory Rate Photoplethysmography Humans Benchmarking Machine Learning Respiration
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