AIMC Topic: Adult

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Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients.

Clinical imaging
PURPOSE: To evaluate performance and the clinical impact of a novel machine learning based vessel-suppressing computer-aided detection (CAD) software in chest computed tomography (CT) of patients with malignant melanoma.

Real-time cardiovascular MR with spatio-temporal artifact suppression using deep learning-proof of concept in congenital heart disease.

Magnetic resonance in medicine
PURPOSE: Real-time assessment of ventricular volumes requires high acceleration factors. Residual convolutional neural networks (CNN) have shown potential for removing artifacts caused by data undersampling. In this study, we investigated the ability...

Association between vitamin D deficiency and insulin resistance markers in euthyroid non-diabetic individuals.

Diabetes & metabolic syndrome
AIM: To evaluate the association between vitamin D deficiency and insulin resistance (IR) or hyperinsulinemia after oral glucose tolerance test (OGTT) in euthyroid non-diabetic individuals.

Prediction of postoperative disease-free survival and brain metastasis for HER2-positive breast cancer patients treated with neoadjuvant chemotherapy plus trastuzumab using a machine learning algorithm.

Breast cancer research and treatment
PURPOSE: This study aimed to develop mathematical tools to predict the likelihood of recurrence after neoadjuvant chemotherapy (NAC) plus trastuzumab in patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer.

Evaluation of Artificial Intelligence-Based Grading of Diabetic Retinopathy in Primary Care.

JAMA network open
IMPORTANCE: There has been wide interest in using artificial intelligence (AI)-based grading of retinal images to identify diabetic retinopathy, but such a system has never been deployed and evaluated in clinical practice.

Value of Neighborhood Socioeconomic Status in Predicting Risk of Outcomes in Studies That Use Electronic Health Record Data.

JAMA network open
IMPORTANCE: Data from electronic health records (EHRs) are increasingly used for risk prediction. However, EHRs do not reliably collect sociodemographic and neighborhood information, which has been shown to be associated with health. The added contri...

A Novel Morphological Analysis of DXA-DICOM Images by Artificial Neural Networks for Estimating Bone Mineral Density in Health and Disease.

Journal of clinical densitometry : the official journal of the International Society for Clinical Densitometry
One of the best methods for diagnosing bone disease in humans is site-specific and total bone mineral density (BMD) measurements by Dual-energy X-ray Absorptiometry (DXA) machines. The basic disadvantage of this technology is inconsistent BMD measure...

Control within a virtual environment is correlated to functional outcomes when using a physical prosthesis.

Journal of neuroengineering and rehabilitation
BACKGROUND: Advances such as targeted muscle reinnervation and pattern recognition control may provide improved control of upper limb myoelectric prostheses, but evaluating user function remains challenging. Virtual environments are cost-effective an...

Demographic and Symptomatic Features of Voice Disorders and Their Potential Application in Classification Using Machine Learning Algorithms.

Folia phoniatrica et logopaedica : official organ of the International Association of Logopedics and Phoniatrics (IALP)
BACKGROUND: Studies have used questionnaires of dysphonic symptoms to screen voice disorders. This study investigated whether the differential presentation of demographic and symptomatic features can be applied to computerized classification.