AIMC Topic: Male

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Argentinian multicenter study on urinary tract infections due to Streptococcus agalactiae in adult patients.

Journal of infection in developing countries
INTRODUCTION: Streptococcus agalactiae (group B streptococcus, GBS) is a recognized urinary pathogen both in males and pregnant or non-pregnant women. Data regarding GBS serotypes recovered from urinary tract infections (UTIs) are scarce. The aim of ...

A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.

Scientific reports
With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have improved, but at the cost of increased treatment plan complexity and planning time. The accurate prediction of dose distributions would alleviate thi...

Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages.

Scientific reports
High-grade gliomas are the most aggressive malignant brain tumors. Accurate pre-operative prognosis for this cohort can lead to better treatment planning. Conventional survival prediction based on clinical information is subjective and could be inacc...

Automatic Tissue Image Segmentation Based on Image Processing and Deep Learning.

Journal of healthcare engineering
Image segmentation plays an important role in multimodality imaging, especially in fusion structural images offered by CT, MRI with functional images collected by optical technologies, or other novel imaging technologies. In addition, image segmentat...

Automatic real-time gait event detection in children using deep neural networks.

PloS one
Annotation of foot-contact and foot-off events is the initial step in post-processing for most quantitative gait analysis workflows. If clean force plate strikes are present, the events can be automatically detected. Otherwise, annotation of gait eve...

Correlating exhaled aerosol images to small airway obstructive diseases: A study with dynamic mode decomposition and machine learning.

PloS one
BACKGROUND: Exhaled aerosols from lungs have unique patterns, and their variation can be correlated to the underlying lung structure and associated abnormities. However, it is challenging to characterize such aerosol patterns and differentiate their ...

Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs.

Journal of pain & palliative care pharmacotherapy
Use of prescription opioids and problems of abuse and addiction have increased over the past decade. Claims-based studies have documented substantial economic burden of opioid abuse. This study utilized electronic health record (EHR) data to identify...

Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.

Academic radiology
RATIONALE AND OBJECTIVES: To use machine learning-based magnetic resonance imaging radiomics to predict metachronous liver metastases (MLM) in patients with rectal cancer.

Water-fat separation and parameter mapping in cardiac MRI via deep learning with a convolutional neural network.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Water-fat separation is a postprocessing technique most commonly applied to multiple-gradient-echo magnetic resonance (MR) images to identify fat, provide images with fat suppression, and to measure fat tissue concentration. Recently, Num...

Machine learning for prediction of sustained opioid prescription after anterior cervical discectomy and fusion.

The spine journal : official journal of the North American Spine Society
BACKGROUND CONTEXT: The severity of the opioid epidemic has increased scrutiny of opioid prescribing practices. Spine surgery is a high-risk episode for sustained postoperative opioid prescription.