AIMC Topic: Female

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Angiography-Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions.

Journal of the American Heart Association Feb 19, 2019
Background An angiography-based supervised machine learning ( ML ) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. Methods and Results With a 4:1 ratio, 1501 patients with 1501 intermediate lesions we...
Coronary Vessels Coronary Stenosis Fractional Flow Reserve, Myocardial Severity of Illness Index ROC Curve Imaging, Three-Dimensional Coronary Angiography Humans Machine Learning Algorithms Retrospective Studies Female Male Middle Aged
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Volumetric analysis of breast cancer tissues using machine learning and swept-source optical coherence tomography.

Applied optics Feb 10, 2019
In breast cancer, 20%-30% of cases require a second surgery because of incomplete excision of malignant tissues. Therefore, to avoid the risk of recurrence, accurate detection of the cancer margin by the clinician or surgeons needs some assistance. I...
Reproducibility of Results Breast Neoplasms Image Processing, Computer-Assisted Support Vector Machine Tomography, Optical Coherence Humans Machine Learning Carcinoma, Ductal, Breast Algorithms Female
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Low coherence quantitative phase microscopy with machine learning model and Raman spectroscopy for the study of breast cancer cells and their classification.

Applied optics Feb 10, 2019
Early-stage detection of breast cancer is the primary requirement in modern healthcare as it is the most common cancer among women worldwide. Histopathology is the most widely preferred method for the diagnosis of breast cancer, but it requires long ...
Interferometry Sensitivity and Specificity Breast Neoplasms ROC Curve Spectrum Analysis, Raman Microscopy, Interference Humans Machine Learning Female Reproducibility of Results
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Efficacy and safety of electroacupuncture in treatment of lumbar disc herniation: a protocol for a cohort study.

Journal of traditional Chinese medicine = Chung i tsa chih ying wen pan Feb 1, 2019
OBJECTIVE: To compare the efficacy of electroacupuncture (deep needling) and general orthopedics in treatment of lumbar disc herniation (LDH), and to evaluate its long-term efficacy.
Surveys and Questionnaires Adolescent Cohort Studies Treatment Outcome Young Adult Humans Moxibustion Lumbar Vertebrae Adult Acupuncture Points Prospective Studies Male Electroacupuncture Female Middle Aged Intervertebral Disc Degeneration Aged Quality of Life Intervertebral Disc Displacement
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Classification of Background Parenchymal Uptake on Molecular Breast Imaging Using a Convolutional Neural Network.

JCO clinical cancer informatics Feb 1, 2019
PURPOSE: Background parenchymal uptake (BPU), which describes the level of radiotracer uptake in normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor. Our objective was to develop and vali...
Breast Radiopharmaceuticals Molecular Imaging Image Interpretation, Computer-Assisted Radionuclide Imaging Parenchymal Tissue Female Risk Factors Breast Neoplasms Risk Assessment Mammography Humans Neural Networks, Computer Algorithms
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Deep Learning for Prediction of AMD Progression: A Pilot Study.

Investigative ophthalmology & visual science Feb 1, 2019
PURPOSE: To develop and assess a method for predicting the likelihood of converting from early/intermediate to advanced wet age-related macular degeneration (AMD) using optical coherence tomography (OCT) imaging and methods of deep learning.
Humans Neural Networks, Computer Machine Learning Female Follow-Up Studies Tomography, Optical Coherence Wet Macular Degeneration Disease Progression Aged Diagnosis, Computer-Assisted Aged, 80 and over Deep Learning Male Pilot Projects Middle Aged ROC Curve
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Network Tomography for Understanding Phenotypic Presentations in Aortic Stenosis.

JACC. Cardiovascular imaging Feb 1, 2019
OBJECTIVES: This study sought to build a patient-patient similarity network using multiple features of left ventricular (LV) structure and function in patients with aortic stenosis (AS). The study further validated the observations in an experimental...
Aortic Valve Stenosis Aortic Valve Predictive Value of Tests Mice, Knockout Heart Ventricles Disease Progression Severity of Illness Index Time Factors Disease Models, Animal Image Interpretation, Computer-Assisted Heart Valve Prosthesis Implantation Balloon Valvuloplasty Female Reproducibility of Results Aged Aged, 80 and over Cross-Sectional Studies Animals Male Ventricular Function, Left Echocardiography Middle Aged Humans Machine Learning
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Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Medicine Feb 1, 2019
Early identification of high-risk septic patients in the emergency department (ED) may guide appropriate management and disposition, thereby improving outcomes. We compared the performance of machine learning models against conventional risk stratifi...
Female Reproducibility of Results Aged Aged, 80 and over Male Humans Machine Learning Singapore Heart Rate Systemic Inflammatory Response Syndrome Organ Dysfunction Scores Middle Aged ROC Curve Severity of Illness Index Socioeconomic Factors Sepsis Triage Hospital Mortality Emergency Service, Hospital
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Artificial intelligence system of faster region-based convolutional neural network surpassing senior radiologists in evaluation of metastatic lymph nodes of rectal cancer.

Chinese medical journal Feb 1, 2019
BACKGROUND: An artificial intelligence system of Faster Region-based Convolutional Neural Network (Faster R-CNN) is newly developed for the diagnosis of metastatic lymph node (LN) in rectal cancer patients. The primary objective of this study was to ...
Neoplasm Recurrence, Local Pathologists Humans Rectal Neoplasms Neural Networks, Computer Male Middle Aged Artificial Intelligence Lymphatic Metastasis Female Neoplasm Staging Aged Radiologists Aged, 80 and over Adult
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CT Image Conversion among Different Reconstruction Kernels without a Sinogram by Using a Convolutional Neural Network.

Korean journal of radiology Feb 1, 2019
OBJECTIVE: The aim of our study was to develop and validate a convolutional neural network (CNN) architecture to convert CT images reconstructed with one kernel to images with different reconstruction kernels without using a sinogram.
Humans Neural Networks, Computer Male Middle Aged Image Processing, Computer-Assisted Pulmonary Emphysema Multidetector Computed Tomography Machine Learning Algorithms Retrospective Studies Female Aged
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