AIMC Topic:
Cross-Sectional Studies

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Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

JAMA ophthalmology Dec 1, 2019
IMPORTANCE: A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.
Cross-Sectional Studies Male Deep Learning ROC Curve Humans Databases, Factual Female Sensitivity and Specificity False Positive Reactions Diagnostic Techniques, Ophthalmological Photography Glaucoma, Open-Angle Predictive Value of Tests Area Under Curve Fundus Oculi Optic Nerve Diseases
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Relevant Features in Nonalcoholic Steatohepatitis Determined Using Machine Learning for Feature Selection.

Metabolic syndrome and related disorders Nov 1, 2019
We investigated the prevalence and the most relevant features of nonalcoholic steatohepatitis (NASH), a stage of nonalcoholic fatty liver disease, (NAFLD) in which the inflammation of hepatocytes can lead to increased cardiovascular risk, liver fibr...
Algorithms Prognosis Retrospective Studies Female Humans Machine Learning Prevalence Severity of Illness Index Diabetes Mellitus, Type 2 Liver Cirrhosis Hypertension Metabolic Syndrome Decision Making Non-alcoholic Fatty Liver Disease Aged Adult Sensitivity and Specificity Cross-Sectional Studies Male Middle Aged Disease Progression
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Sarcopenia feature selection and risk prediction using machine learning: A cross-sectional study.

Medicine Oct 1, 2019
The purpose of this study was to verify the usefulness of machine learning (ML) for selection of risk factors and development of predictive models for patients with sarcopenia.We collected medical records from Korean postmenopausal women based on Kor...
Aged Cross-Sectional Studies Risk Assessment Nutrition Surveys Machine Learning Republic of Korea Female Risk Factors Sarcopenia Postmenopause Humans
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Artificial Intelligence Treatment Decision Support For Complex Breast Cancer Among Oncologists With Varying Expertise.

JCO clinical cancer informatics Aug 1, 2019
PURPOSE: The aim of the current study was to assess treatment concordance and adherence to National Comprehensive Cancer Network breast cancer treatment guidelines between oncologists and an artificial intelligence advisory tool.
Reproducibility of Results Breast Neoplasms Biomarkers, Tumor Cross-Sectional Studies Clinical Competence Decision Support Systems, Clinical Guideline Adherence Neoplasm Staging Humans Artificial Intelligence Clinical Decision-Making Female Medical Oncology Practice Guidelines as Topic Practice Patterns, Physicians' Oncologists
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Underserved populations with missing race ethnicity data differ significantly from those with structured race/ethnicity documentation.

Journal of the American Medical Informatics Association : JAMIA Aug 1, 2019
OBJECTIVE: We aimed to address deficiencies in structured electronic health record (EHR) data for race and ethnicity by identifying black and Hispanic patients from unstructured clinical notes and assessing differences between patients with or withou...
Humans Cross-Sectional Studies Hispanic or Latino Algorithms Male Ethnicity Electronic Health Records Vulnerable Populations Black or African American Female Natural Language Processing Racial Groups
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Assessment of Usability and Task Load Demand Using a Robot-Assisted Transfer Device Compared With a Hoyer Advance for Dependent Wheelchair Transfers.

American journal of physical medicine & rehabilitation Aug 1, 2019
OBJECTIVE: Manual lifting can be burdensome for people who care for power wheelchair users. Although technologies used for dependent transfers are helpful, they have shortcomings of their own. This study compares the usability and task load demand of...
Robotics Equipment Design Caregivers Wheelchairs Self-Help Devices Weight-Bearing Moving and Lifting Patients Adult Humans Cross-Sectional Studies Female Male Young Adult Middle Aged
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Automatic extraction of imaging observation and assessment categories from breast magnetic resonance imaging reports with natural language processing.

Chinese medical journal Jul 20, 2019
BACKGROUND: Structured reports are not widely used and thus most reports exist in the form of free text. The process of data extraction by experts is time-consuming and error-prone, whereas data extraction by natural language processing (NLP) is a po...
Magnetic Resonance Imaging Natural Language Processing Breast Humans Algorithms Female Adult Cross-Sectional Studies Middle Aged
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Data Representations for Segmentation of Vascular Structures Using Convolutional Neural Networks with U-Net Architecture.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Convolutional neural networks (CNNs) produce promising results when applied to a wide range of medical imaging tasks including the segmentation of tissue structures. However, segmentation is particularly challenging when the target structures are sma...
Cross-Sectional Studies Humans Image Processing, Computer-Assisted Neural Networks, Computer Tomography, X-Ray Computed
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An artificial neural network model for clinical score prediction in Alzheimer disease using structural neuroimaging measures.

Journal of psychiatry & neuroscience : JPN Jul 1, 2019
BACKGROUND: The development of diagnostic and prognostic tools for Alzheimer disease is complicated by substantial clinical heterogeneity in prodromal stages. Many neuroimaging studies have focused on case–control classification and predicting conver...
Neuroimaging Cerebral Cortex Proof of Concept Study Humans Neural Networks, Computer Female Reproducibility of Results Severity of Illness Index Aged Longitudinal Studies Aged, 80 and over Magnetic Resonance Imaging Cross-Sectional Studies Alzheimer Disease Male
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[Artificial intelligence in medicine-the wrong track or promise of cure?].

HNO May 1, 2019
Artificial intelligence (AI) has attained a new level of maturity in recent years and is developing into the driver of digitalization in all areas of life. AI is a cross-sectional technology with great importance for all branches of medicine employin...
Humans Decision Making, Computer-Assisted Artificial Intelligence Cross-Sectional Studies
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