AIMC Topic: Prospective Studies

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Machine learning-based multiparametric MRI radiomics for predicting the aggressiveness of papillary thyroid carcinoma.

European journal of radiology
PURPOSE: To investigate the predictive capability of machine learning-based multiparametric magnetic resonance (MR) imaging radiomics for evaluating the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively.

Pelvic lymph node dissection at robot-assisted radical prostatectomy: Assessing utilization and nodal metastases within a statewide quality improvement consortium.

Urologic oncology
PURPOSE: Several guidelines recommend pelvic lymph node dissection (PLND) at robot-assisted radical prostatectomy (RARP) only when lymph node involvement (LN+) is >2%. Individual surgeon use of PLND is not well-known. We sought to examine variability...

Prospective prediction of suicide attempts in community adolescents and young adults, using regression methods and machine learning.

Journal of affective disorders
BACKGROUND: The use of machine learning (ML) algorithms to study suicidality has recently been recommended. Our aim was to explore whether ML approaches have the potential to improve the prediction of suicide attempt (SA) risk. Using the epidemiologi...

Patients' views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire.

European radiology
OBJECTIVES: The patients' view on the implementation of artificial intelligence (AI) in radiology is still mainly unexplored territory. The aim of this article is to develop and validate a standardized patient questionnaire on the implementation of A...

Prospective evaluation of clarithromycin in recurrent chronic rhinosinusitis with nasal polyps.

Brazilian journal of otorhinolaryngology
INTRODUCTION: The antiinflammatory effects of macrolides, especially clarithromycin, have been described in patients with chronic rhinosinusitis without polyps and also other chronic inflammatory airway diseases. There is no consensus in the literatu...

Machine-learning-derived rules set excludes risk of Parkinson's disease in patients with olfactory or gustatory symptoms with high accuracy.

Journal of neurology
BACKGROUND: Chemosensory loss is a symptom of Parkinson's disease starting already at preclinical stages. Their appearance without an identifiable etiology therefore indicates a possible early symptom of Parkinson's disease. Supervised machine-learni...

Application of machine learning to determine top predictors of noncalcified coronary burden in psoriasis: An observational cohort study.

Journal of the American Academy of Dermatology
BACKGROUND: Psoriasis is associated with elevated risk of heart attack and increased accumulation of subclinical noncalcified coronary burden by coronary computed tomography angiography (CCTA). Machine learning algorithms have been shown to effective...

Correlation of machine learning computed tomography-based fractional flow reserve with instantaneous wave free ratio to detect hemodynamically significant coronary stenosis.

Clinical research in cardiology : official journal of the German Cardiac Society
BACKGROUND: Fractional flow reserve based on coronary CT angiography (CT-FFR) is gaining importance for non-invasive hemodynamic assessment of coronary artery disease (CAD). We evaluated the on-site CT-FFR with a machine learning algorithm (CT-FFR) f...