AIMC Topic: Adolescent

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Prediction of vascular aging based on smartphone acquired PPG signals.

Scientific reports
Photoplethysmography (PPG) measured by smartphone has the potential for a large scale, non-invasive, and easy-to-use screening tool. Vascular aging is linked to increased arterial stiffness, which can be measured by PPG. We investigate the feasibilit...

Machine learning approaches for sex estimation using cranial measurements.

International journal of legal medicine
The aim of the present study is to apply support vector machines (SVM) and artificial neural network (ANN) as sex classifiers and to generate useful classification models for sex estimation based on cranial measurements. Besides, the performance of t...

Machine-learning algorithms for predicting hospital re-admissions in sickle cell disease.

British journal of haematology
Reducing preventable hospital re-admissions in Sickle Cell Disease (SCD) could potentially improve outcomes and decrease healthcare costs. In a retrospective study of electronic health records, we hypothesized Machine-Learning (ML) algorithms may out...

Association of a Serum Protein Signature With Rheumatoid Arthritis Development.

Arthritis & rheumatology (Hoboken, N.J.)
OBJECTIVE: The pathophysiologic events that precede the onset of rheumatoid arthritis (RA) remain incompletely understood. This study was undertaken to identify changes in the serum proteome that precede the onset of RA, with the aim of providing new...

Comparing machine learning with case-control models to identify confirmed dengue cases.

PLoS neglected tropical diseases
In recent decades, the global incidence of dengue has increased. Affected countries have responded with more effective surveillance strategies to detect outbreaks early, monitor the trends, and implement prevention and control measures. We have appli...

A Random Forest Machine Learning Framework to Reduce Running Injuries in Young Triathletes.

Sensors (Basel, Switzerland)
BACKGROUND: The running segment of a triathlon produces 70% of the lower limb injuries. Previous research has shown a clear association between kinematic patterns and specific injuries during running.

Cross-site transportability of an explainable artificial intelligence model for acute kidney injury prediction.

Nature communications
Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability. Non-interoperable data across hospitals is a major barrier to mo...

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, ...

Assessment of Facial Morphologic Features in Patients With Congenital Adrenal Hyperplasia Using Deep Learning.

JAMA network open
IMPORTANCE: Congenital adrenal hyperplasia (CAH) is the most common primary adrenal insufficiency in children, involving excess androgens secondary to disrupted steroidogenesis as early as the seventh gestational week of life. Although structural bra...