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Precision medicine and machine learning towards the prediction of the outcome of potential celiac disease.

Scientific reports
Potential Celiac Patients (PCD) bear the Celiac Disease (CD) genetic predisposition, a significant production of antihuman transglutaminase antibodies, but no morphological changes in the small bowel mucosa. A minority of patients (17%) showed clinic...

Predicting Parkinson's disease trajectory using clinical and neuroimaging baseline measures.

Parkinsonism & related disorders
INTRODUCTION: Predictive biomarkers of Parkinson's Disease progression are needed to expedite neuroprotective treatment development and facilitate prognoses for patients. This work uses measures derived from resting-state functional magnetic resonanc...

Assessment of an Exhaled Breath Test Using High-Pressure Photon Ionization Time-of-Flight Mass Spectrometry to Detect Lung Cancer.

JAMA network open
IMPORTANCE: Exhaled breath is an attractive option for cancer detection. A sensitive and reliable breath test has the potential to greatly facilitate diagnoses and therapeutic monitoring of lung cancer.

Development of a Machine Learning Model Using Electronic Health Record Data to Identify Antibiotic Use Among Hospitalized Patients.

JAMA network open
IMPORTANCE: Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve compariso...

Machine Learning Assessment of Early Life Factors Predicting Suicide Attempt in Adolescence or Young Adulthood.

JAMA network open
IMPORTANCE: Although longitudinal studies have reported associations between early life factors (ie, in-utero/perinatal/infancy) and long-term suicidal behavior, they have concentrated on 1 or few selected factors, and established associations, but d...

A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease.

Scientific reports
Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and progression detection have been intensively studied. Nevertheless, research studies often have little effect on clinical practice mainly due to the following reasons: (1)...

Deep convolutional neural networks to predict cardiovascular risk from computed tomography.

Nature communications
Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment....

Predicting Incremental and Future Visual Change in Neovascular Age-Related Macular Degeneration Using Deep Learning.

Ophthalmology. Retina
PURPOSE: To evaluate the predictive usefulness of quantitative imaging biomarkers, acquired automatically from OCT scans, of cross-sectional and future visual outcomes of patients with neovascular age-related macular degeneration (AMD) starting anti-...