AIMC Topic: Prospective Studies

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Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning ha...

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

La Radiologia medica
OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate canc...

Machine learning methodologies versus cardiovascular risk scores, in predicting disease risk.

BMC medical research methodology
BACKGROUND: The use of Cardiovascular Disease (CVD) risk estimation scores in primary prevention has long been established. However, their performance still remains a matter of concern. The aim of this study was to explore the potential of using ML m...

Automated, machine learning-based, 3D echocardiographic quantification of left ventricular mass.

Echocardiography (Mount Kisco, N.Y.)
BACKGROUND: Although 3D echocardiography (3DE) circumvents many limitations of 2D echocardiography by allowing direct measurements of left ventricular (LV) mass, it is seldom used in clinical practice due to time-consuming analysis. A recently develo...

A signature-based machine learning model for distinguishing bipolar disorder and borderline personality disorder.

Translational psychiatry
Mobile technologies offer new opportunities for prospective, high resolution monitoring of long-term health conditions. The opportunities seem of particular promise in psychiatry where diagnoses often rely on retrospective and subjective recall of mo...

Applied Force during Piston Prosthesis Placement in a 3D-Printed Model: Freehand vs Robot-Assisted Techniques.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
OBJECTIVES: To describe a 3D-printed middle ear model that quantifies the force applied to the modeled incus. To compare the forces applied during placement and crimping of a stapes prosthesis between the Robotic ENT Microsurgery System ( REMS) and t...

In vitro activity of tedizolid and other comparator drugs in methicillin-resistant Staphylococcus aureus isolates in skin and soft tissue infections in seven Colombian hospitals.

Biomedica : revista del Instituto Nacional de Salud
Introduction: Methicillin-resistant Staphylococcus aureus (MRSA) causes severe skin and soft tissue infections in hospitals and, more recently, in the community. Tedizolid is a new second-generation oxazolidinone derivative having greater in vitro po...

A prospective study evaluating impact on renal function following percutaneous nephrolithotomy using Tc99m ethylenedicysteine renal scan: Does multiplicity of access tracts play a role?

Investigative and clinical urology
PURPOSE: A prospective study evaluating impact of percutaneous nephrolithotomy (PCNL) on renal function following PCNL using ethylenedicysteine (EC) renal scan. Does multiplicity of access tracts play a role?

Mobile detection of autism through machine learning on home video: A development and prospective validation study.

PLoS medicine
BACKGROUND: The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. This has in part contributed to long wait times for a diagnosis and subsequent delays in access...