AIMC Topic: Reproducibility of Results

Clear Filters Showing 4581 to 4590 of 5908 articles

Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks.

Medical image analysis
The amount of coronary artery calcification (CAC) is a strong and independent predictor of cardiovascular events. CAC is clinically quantified in cardiac calcium scoring CT (CSCT), but it has been shown that cardiac CT angiography (CCTA) may also be ...

A self-taught artificial agent for multi-physics computational model personalization.

Medical image analysis
Personalization is the process of fitting a model to patient data, a critical step towards application of multi-physics computational models in clinical practice. Designing robust personalization algorithms is often a tedious, time-consuming, model- ...

Computer-based coding of free-text job descriptions to efficiently identify occupations in epidemiological studies.

Occupational and environmental medicine
BACKGROUND: Mapping job titles to standardised occupation classification (SOC) codes is an important step in identifying occupational risk factors in epidemiological studies. Because manual coding is time-consuming and has moderate reliability, we de...

Drug target identification using network analysis: Taking active components in Sini decoction as an example.

Scientific reports
Identifying the molecular targets for the beneficial effects of active small-molecule compounds simultaneously is an important and currently unmet challenge. In this study, we firstly proposed network analysis by integrating data from network pharmac...

Modeling and optimization of anaerobic codigestion of potato waste and aquatic weed by response surface methodology and artificial neural network coupled genetic algorithm.

Bioresource technology
A novel approach to overcome the acidification problem has been attempted in the present study by codigesting industrial potato waste (PW) with Pistia stratiotes (PS, an aquatic weed). The effectiveness of codigestion of the weed and PW was tested in...

Prediction of Cascading Failures in Spatial Networks.

PloS one
Cascading overload failures are widely found in large-scale parallel systems and remain a major threat to system reliability; therefore, they are of great concern to maintainers and managers of different systems. Accurate cascading failure prediction...

Respiratory Artefact Removal in Forced Oscillation Measurements: A Machine Learning Approach.

IEEE transactions on bio-medical engineering
GOAL: Respiratory artefact removal for the forced oscillation technique can be treated as an anomaly detection problem. Manual removal is currently considered the gold standard, but this approach is laborious and subjective. Most existing automated t...

Computer-Aided Diagnosis with Deep Learning Architecture: Applications to Breast Lesions in US Images and Pulmonary Nodules in CT Scans.

Scientific reports
This paper performs a comprehensive study on the deep-learning-based computer-aided diagnosis (CADx) for the differential diagnosis of benign and malignant nodules/lesions by avoiding the potential errors caused by inaccurate image processing results...

Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease.

IEEE transactions on bio-medical engineering
Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer's disease and its prodromal stage, i.e., mild cognitive impairment. However, most existing sparse learning-based studies only adopt cross-s...

High-throughput liquid chromatography tandem mass spectrometry method for simultaneous determination of fampridine, paroxetine, and quinidine in rat plasma: Application to in vivo perfusion study.

Journal of food and drug analysis
A selective and high-throughput liquid chromatography-mass spectrometry method has been developed and validated for the simultaneous quantification of paroxetine, fampridine, and quinidine in rat plasma using imipramine as an internal standard. Follo...