AIMC Topic: Prospective Studies

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Machine Learning-Based Prediction of Clinical Outcomes in Patients With Cancer Receiving Systemic Treatment Using Step Count Data Measured With Smartphones.

JCO clinical cancer informatics
PURPOSE: This study aimed to investigate whether changes in step count, measured using patients' own smartphones, could predict a clinical adverse event in the upcoming week in patients undergoing systemic anticancer treatments using machine learning...

Early detection of Alzheimer's disease using small RNAs. Results from the EPAD cohort.

The journal of prevention of Alzheimer's disease
BACKGROUND: Alzheimer's disease (AD) is the most common form of dementia, and early diagnosis is crucial to enable effective interventions. Currently, Alzheimer's disease is diagnosed through cognitive assessments, brain imaging and fluid biomarkers ...

Task-specific versus general-purpose AI models in ECG analysis: A comparative study with emergency medicine specialists.

The American journal of emergency medicine
PURPOSE: To evaluate and compare the diagnostic accuracy of three Artificial intelligence (AI) models-GPT-4o, Canva-GPT, and ECG Reader-GPT-against emergency medicine specialists (EMSs) in electrocardiogram (ECG) interpretation using a standardized a...

Radiomic 'Stress Test': exploration of a deep learning radiomic model in a high-risk prospective lung nodule cohort.

BMJ open respiratory research
BACKGROUND: Indeterminate pulmonary nodules (IPNs) are commonly biopsied to ascertain a diagnosis of lung cancer, but many are ultimately benign. The Lung Cancer Prediction (LCP) score is a commercially available deep learning radiomic model with str...

Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recognition: Protocol for a Prospective Cohort Study.

JMIR research protocols
BACKGROUND: Substance use disorder (SUD) involves excessive substance consumption and persistent reward-seeking behaviors, leading to serious physical, cognitive, and social consequences. This disorder is a global health crisis tied to increased mort...

From laser-on time to lithotripsy duration: improving the prediction of lithotripsy duration with 'Kidney Stone Calculator' using artificial intelligence.

World journal of urology
INTRODUCTION: "Kidney Stone Calculator" (KSC) helps to plan flexible ureteroscopy, providing the stone volume (SV) and an estimated duration of laser lithotripsy (eLD). eLD is calculated from in vitro ablation rates and SV. KSC's accuracy has been de...

Epicardial adipose tissue, myocardial remodelling and adverse outcomes in asymptomatic aortic stenosis: a post hoc analysis of a randomised controlled trial.

Heart (British Cardiac Society)
BACKGROUND: Epicardial adipose tissue represents a metabolically active visceral fat depot that is in direct contact with the left ventricular myocardium. While it is associated with coronary artery disease, little is known regarding its role in aort...

Evaluating real-world performance of an automated offline glaucoma AI on a smartphone fundus camera across glaucoma severity stages.

PloS one
PURPOSE: Leveraging an artificial intelligence system (AI) for glaucoma screening can mitigate the current challenges and provide prompt detection and management crucial in averting irreversible blindness. The study reports the real-world performance...

Progression and natural history of Atypical Parkinsonism (ATPARK): Protocol for a longitudinal follow-up study from an underrepresented population.

PloS one
BACKGROUND: Atypical Parkinsonian Syndromes (APS) form the third largest group of neurodegenerative disorders including Progressive Supranuclear Palsy (PSP), Multiple System Atrophy (MSA), and Corticobasal Syndrome (CBS). These conditions are charact...

Computed tomography-derived quantitative imaging biomarkers enable the prediction of disease manifestations and survival in patients with systemic sclerosis.

RMD open
INTRODUCTION: Systemic sclerosis (SSc) is a complex inflammatory vasculopathy with diverse symptoms and variable disease progression. Despite its known impact on body composition (BC), clinical decision-making has yet to incorporate these biomarkers....