AIMC Topic: Adolescent

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Brain Age in Early Stages of Bipolar Disorders or Schizophrenia.

Schizophrenia bulletin
BACKGROUND: The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resona...

Predicting individual physiologically acceptable states at discharge from a pediatric intensive care unit.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Quantify physiologically acceptable PICU-discharge vital signs and develop machine learning models to predict these values for individual patients throughout their PICU episode.

A Dual-Accelerometer System for Classifying Physical Activity in Children and Adults.

Medicine and science in sports and exercise
INTRODUCTION: Accurately monitoring 24-h movement behaviors is a vital step for progressing the time-use epidemiology field. Past accelerometer-based measurement protocols are either hindered by lack of wear time compliance, or the inability to accur...

Automated Risk Assessment for School Violence: a Pilot Study.

The Psychiatric quarterly
School violence has increased over the past ten years. This study evaluated students using a more standard and sensitive method to help identify students who are at high risk for school violence. 103 participants were recruited through Cincinnati Chi...

Artificial intelligence-derived 3-Way Concentration-dependent Antagonism of Gatifloxacin, Pyrazinamide, and Rifampicin During Treatment of Pulmonary Tuberculosis.

Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
BACKGROUND: In the experimental arm of the OFLOTUB trial, gatifloxacin replaced ethambutol in the standard 4-month regimen for drug-susceptible pulmonary tuberculosis. The study included a nested pharmacokinetic (PK) study. We sought to determine if ...

The role of presepsin in the diagnosis and assessment of severity of sepsis and severe pneumonia.

Terapevticheskii arkhiv
AIM: The aim of this study was to evaluate marker of inflammation presepsin to improve diagnosis of severe pneumonia, sepsis.

[Robot assisted sacroiliac screw placement with a modified method of screw path planning].

Zhonghua yi xue za zhi
To introduce a robot-assisted modified method of sacroiliac screw path planning in order to reduce the incidence of screw misplacement. The study involved 13 patients suffering from posterior pelvic injuries treated by percutaneous sacroiliac screw...

A machine learning approach to predict early outcomes after pituitary adenoma surgery.

Neurosurgical focus
OBJECTIVEPituitary adenomas occur in a heterogeneous patient population with diverse perioperative risk factors, endocrinopathies, and other tumor-related comorbidities. This heterogeneity makes predicting postoperative outcomes challenging when usin...

Machine-learning analysis outperforms conventional statistical models and CT classification systems in predicting 6-month outcomes in pediatric patients sustaining traumatic brain injury.

Neurosurgical focus
OBJECTIVEModern surgical planning and prognostication requires the most accurate outcomes data to practice evidence-based medicine. For clinicians treating children following traumatic brain injury (TBI) these data are severely lacking. The first aim...

Estimating Normal Values of Rare T-Lymphocyte Populations in Peripheral Blood of Healthy Cuban Adults.

MEDICC review
INTRODUCTION Flow cytometry allows immunophenotypic characterization of important lymphocyte subpopulations for diagnosis of diseases such as cancer, autoimmune diseases, immunodeficiencies and some infections. Normal values of rare lymphoid cells in...