AIMC Topic: Sensitivity and Specificity

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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- ...

Folded concave penalized learning in identifying multimodal MRI marker for Parkinson's disease.

Journal of neuroscience methods
BACKGROUND: Brain MRI holds promise to gauge different aspects of Parkinson's disease (PD)-related pathological changes. Its analysis, however, is hindered by the high-dimensional nature of the data.

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...

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...

Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes.

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
OBJECTIVE: Delayed diagnosis of Kawasaki disease (KD) may lead to serious cardiac complications. We sought to create and test the performance of a natural language processing (NLP) tool, the KD-NLP, in the identification of emergency department (ED) ...

Monitoring of total positive end-expiratory pressure during mechanical ventilation by artificial neural networks.

Journal of clinical monitoring and computing
Ventilation treatment of acute lung injury (ALI) requires the application of positive airway pressure at the end of expiration (PEEP) to avoid lung collapse. However, the total pressure exerted on the alveolar walls (PEEP) is the sum of PEEP and intr...

Improve Glioblastoma Multiforme Prognosis Prediction by Using Feature Selection and Multiple Kernel Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Glioblastoma multiforme (GBM) is a highly aggressive type of brain cancer with very low median survival. In order to predict the patient's prognosis, researchers have proposed rules to classify different glioma cancer cell subtypes. However, survival...

Identifying children with autism spectrum disorder based on their face processing abnormality: A machine learning framework.

Autism research : official journal of the International Society for Autism Research
The atypical face scanning patterns in individuals with Autism Spectrum Disorder (ASD) has been repeatedly discovered by previous research. The present study examined whether their face scanning patterns could be potentially useful to identify childr...

Development of two artificial neural network models to support the diagnosis of pulmonary tuberculosis in hospitalized patients in Rio de Janeiro, Brazil.

Medical & biological engineering & computing
Pulmonary tuberculosis (PTB) remains a worldwide public health problem. Diagnostic algorithms to identify the best combination of diagnostic tests for PTB in each setting are needed for resource optimization. We developed one artificial neural networ...

A decision support system to improve medical diagnosis using a combination of k-medoids clustering based attribute weighting and SVM.

Journal of medical systems
The use of machine learning tools has become widespread in medical diagnosis. The main reason for this is the effective results obtained from classification and diagnosis systems developed to help medical professionals in the diagnosis phase of disea...