AIMC Topic: Cohort Studies

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Early-life and concurrent predictors of the healthy adolescent microbiome in a cohort study.

Genome medicine
BACKGROUND: The microbiome of adolescents is poorly understood, as are factors influencing its composition. We aimed to describe the healthy adolescent microbiome and identify early-life and concurrent predictors of its composition.

Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH.

Respiratory research
BACKGROUND: Classification of the etiologies of pleural effusion is a critical challenge in clinical practice. Traditional diagnostic methods rely on a simple cut-off method based on the laboratory tests. However, machine learning (ML) offers a novel...

Predicting Agitation Events in the Emergency Department Through Artificial Intelligence.

JAMA network open
IMPORTANCE: Agitation events are increasing in emergency departments (EDs), exacerbating safety risks for patients and clinicians. A wide range of clinical etiologies and behavioral patterns in the emergency setting make agitation prediction difficul...

Dual-stream algorithms for dementia detection: Harnessing structured and unstructured electronic health record data, a novel approach to prevalence estimation.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Identifying individuals with dementia is crucial for prevalence estimation and service planning, but reliable, scalable methods are lacking. We developed novel set algorithms using both structured and unstructured electronic health reco...

Machine Learning Predicts Risk of Falls in Parkison's Disease Patients in a Multicenter Observational Study.

European journal of neurology
BACKGROUND: Postural instability and gait difficulties are key symptoms of Parkinson's disease (PD), elevating the risk of falls substantially. Falls afflict 35% to 90% of PD patients, representing a major challenge in managing the condition. Accurat...

Automated Imaging Differentiation for Parkinsonism.

JAMA neurology
IMPORTANCE: Magnetic resonance imaging (MRI) paired with appropriate disease-specific machine learning holds promise for the clinical differentiation of Parkinson disease (PD), multiple system atrophy (MSA) parkinsonian variant, and progressive supra...

Predicting Diagnostic Progression to Schizophrenia or Bipolar Disorder via Machine Learning.

JAMA psychiatry
IMPORTANCE: The diagnosis of schizophrenia and bipolar disorder is often delayed several years despite illness typically emerging in late adolescence or early adulthood, which impedes initiation of targeted treatment.

Determinants of ascending aortic morphology: cross-sectional deep learning-based analysis on 25 073 non-contrast-enhanced NAKO MRI studies.

European heart journal. Cardiovascular Imaging
AIMS: Understanding determinants of thoracic aortic morphology is crucial for precise diagnostics and therapeutic approaches. This study aimed to automatically characterize ascending aortic morphology based on 3D non-contrast-enhanced magnetic resona...

Robust Diagnosis of Acute Bacterial and Viral Infections via Host Gene Expression Rank-Based Ensemble Machine Learning Algorithm: A Multi-Cohort Model Development and Validation Study.

Clinical chemistry
BACKGROUND: The accurate and prompt diagnosis of infections is essential for improving patient outcomes and preventing bacterial drug resistance. Host gene expression profiling as an approach to infection diagnosis holds great potential in assisting ...

Artificial Intelligence-Enabled Wearable Devices and Nocturnal Scratching in Mild Atopic Dermatitis.

JAMA dermatology
IMPORTANCE: Although more than 1 in 10 people experience pruritus, there are limited medical technologies that can accurately and continuously quantify and simultaneously reduce scratching behaviors through nonpharmacological methods.