AIMC Topic: Sensitivity and Specificity

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Machine learning for detection of stenoses and aneurysms: application in a physiologically realistic virtual patient database.

Biomechanics and modeling in mechanobiology
This study presents an application of machine learning (ML) methods for detecting the presence of stenoses and aneurysms in the human arterial system. Four major forms of arterial disease-carotid artery stenosis (CAS), subclavian artery stenosis (SAS...

Early detection of COVID-19 in the UK using self-reported symptoms: a large-scale, prospective, epidemiological surveillance study.

The Lancet. Digital health
BACKGROUND: Self-reported symptoms during the COVID-19 pandemic have been used to train artificial intelligence models to identify possible infection foci. To date, these models have only considered the culmination or peak of symptoms, which is not s...

Machine learning to predict distal caries in mandibular second molars associated with impacted third molars.

Scientific reports
Impacted mandibular third molars (M3M) are associated with the occurrence of distal caries on the adjacent mandibular second molars (DCM2M). In this study, we aimed to develop and validate five machine learning (ML) models designed to predict the occ...

Prediction of Drug-Induced Liver Toxicity Using SVM and Optimal Descriptor Sets.

International journal of molecular sciences
Drug-induced liver toxicity is one of the significant safety challenges for the patient's health and the pharmaceutical industry. It causes termination of drug candidates in clinical trials and also the retractions of approved drugs from the market. ...

Diagnosis of retinal disorders from Optical Coherence Tomography images using CNN.

PloS one
An efficient automatic decision support system for detection of retinal disorders is important and is the need of the hour. Optical Coherence Tomography (OCT) is the current imaging modality for the early detection of retinal disorders non-invasively...

Clinically applicable artificial intelligence system for dental diagnosis with CBCT.

Scientific reports
In this study, a novel AI system based on deep learning methods was evaluated to determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks, pathologies, clinical effectiveness, and safety when used by dentists in a clinica...

Prediction model for malignant pulmonary nodules based on cfMeDIP-seq and machine learning.

Cancer science
Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) is a new bisulfite-free technique, which can detect the whole-genome methylation of blood cell-free DNA (cfDNA). Using this technique, we identified differentia...

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.

PLoS computational biology
Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used...

Affective State during Physiotherapy and Its Analysis Using Machine Learning Methods.

Sensors (Basel, Switzerland)
Invasive or uncomfortable procedures especially during healthcare trigger emotions. Technological development of the equipment and systems for monitoring and recording psychophysiological functions enables continuous observation of changes to a situa...