AIMC Topic: Female

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Broad Learning Enhanced H-MRS for Early Diagnosis of Neuropsychiatric Systemic Lupus Erythematosus.

Computational and mathematical methods in medicine
In this paper, we explore the potential of using the multivoxel proton magnetic resonance spectroscopy (H-MRS) to diagnose neuropsychiatric systemic lupus erythematosus (NPSLE) with the assistance of a support vector machine broad learning system (BL...

Improvement of late gadolinium enhancement image quality using a deep learning-based reconstruction algorithm and its influence on myocardial scar quantification.

European radiology
OBJECTIVES: The aim of this study was to assess the effect of a deep learning (DL)-based reconstruction algorithm on late gadolinium enhancement (LGE) image quality and to evaluate its influence on scar quantification.

Deep Learning for Voice Gender Identification: Proof-of-concept for Gender-Affirming Voice Care.

The Laryngoscope
OBJECTIVES/HYPOTHESIS: The need for gender-affirming voice care has been increasing in the transgender population in the last decade. Currently, objective treatment outcome measurements are lacking to assess the success of these interventions. This s...

Age verification using random forests on facial 3D landmarks.

Forensic science international
Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and veri...

Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice.

European journal of radiology
PURPOSE: To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic ...

Predictive score for complete occlusion of intracranial aneurysms treated by flow-diverter stents using machine learning.

Journal of neurointerventional surgery
BACKGROUND: Complete occlusion of an intracranial aneurysm (IA) after the deployment of a flow-diverter stent is currently unpredictable. The aim of this study was to develop a predictive occlusion score based on pretreatment clinical and angiographi...

Deep learning enabled prediction of 5-year survival in pediatric genitourinary rhabdomyosarcoma.

Surgical oncology
BACKGROUND: Genitourinary rhabdomyosarcoma (GU-RMS) is a rare, pediatric malignancy originating from embryonic mesenchyme. Current approaches to prognostication rely upon conventional statistical methods such as Cox proportional hazards (CPH) models ...

Identification of Latent Risk Clinical Attributes for Children Born Under IUGR Condition Using Machine Learning Techniques.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disord...

Mammography Image Quality Assurance Using Deep Learning.

IEEE transactions on bio-medical engineering
OBJECTIVE: According to the European Reference Organization for Quality Assured Breast Cancer Screening and Diagnostic Services (EUREF) image quality in mammography is assessed by recording and analyzing a set of images of the CDMAM phantom. The EURE...