AIMC Topic: Case-Control Studies

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Identification of esophageal cancer pathway deviation and construction of a diagnosis model using three kernel genes.

Journal of cellular physiology Mar 5, 2019
The purpose of this study is to better understand the role of interleukin 35 (IL35) in esophageal carcinoma by comparing the mRNA level in Barrett's esophageal mucosa and in matched normal squamous mucosa and to understand how the diagnosis model wor...
Gene Expression Profiling Transcriptome Case-Control Studies Deep Learning Gene Expression Regulation, Neoplastic Humans Reproducibility of Results Biomarkers, Tumor Esophageal Neoplasms Cyclic AMP Response Element-Binding Protein Esophageal Squamous Cell Carcinoma Hepatocyte Nuclear Factor 1-beta Interleukin-12 Subunit p35 Models, Genetic Databases, Genetic Early Detection of Cancer Nerve Tissue Proteins Predictive Value of Tests
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Scaled Subprofile Modeling and Convolutional Neural Networks for the Identification of Parkinson's Disease in 3D Nuclear Imaging Data.

International journal of neural systems Mar 3, 2019
Over the last years convolutional neural networks (CNNs) have shown remarkable results in different image classification tasks, including medical imaging. One area that has been less explored with CNNs is Positron Emission Tomography (PET). Fluorodeo...
Aged Fluorodeoxyglucose F18 Humans Neural Networks, Computer Male Imaging, Three-Dimensional Brain Middle Aged Parkinson Disease Female Case-Control Studies Models, Statistical Functional Neuroimaging Principal Component Analysis Positron-Emission Tomography
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U-Net based deep learning bladder segmentation in CT urography.

Medical physics Feb 28, 2019
OBJECTIVES: To develop a U-Net-based deep learning approach (U-DL) for bladder segmentation in computed tomography urography (CTU) as a part of a computer-assisted bladder cancer detection and treatment response assessment pipeline.
Algorithms Tomography, X-Ray Computed Case-Control Studies Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Urinary Bladder Neoplasms Urinary Bladder Urography
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Natural language processing and machine learning algorithm to identify brain MRI reports with acute ischemic stroke.

PloS one Feb 28, 2019
BACKGROUND AND PURPOSE: This project assessed performance of natural language processing (NLP) and machine learning (ML) algorithms for classification of brain MRI radiology reports into acute ischemic stroke (AIS) and non-AIS phenotypes.
Retrospective Studies Natural Language Processing Female Middle Aged Image Interpretation, Computer-Assisted Humans Aged Case-Control Studies Random Allocation Adult Brain Support Vector Machine Brain Infarction Male Magnetic Resonance Imaging Decision Trees
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EEG-based mild depression recognition using convolutional neural network.

Medical & biological engineering & computing Feb 19, 2019
Electroencephalography (EEG)-based studies focus on depression recognition using data mining methods, while those on mild depression are yet in infancy, especially in effective monitoring and quantitative measure aspects. Aiming at mild depression re...
Emotions Humans Electroencephalography Depression Neural Networks, Computer Electrodes Adolescent Algorithms Female Time Factors Young Adult Image Processing, Computer-Assisted Male Case-Control Studies Diagnosis, Computer-Assisted
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Pancreatic cancer biomarker detection by two support vector strategies for recursive feature elimination.

Biomarkers in medicine Feb 15, 2019
AIM: Pancreatic cancer is one of the worst malignant tumors in prognosis. Therefore, to reduce the mortality rate of pancreatic cancer, early diagnosis and prompt treatment are particularly important.
Matrix Metalloproteinase 7 alpha-Macroglobulins Prognosis Survival Rate Humans Biomarkers, Tumor Case-Control Studies Algorithms Support Vector Machine Gene Expression Profiling Pancreatic Neoplasms Pancreas Proto-Oncogene Proteins c-fos
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Severe Dengue Prognosis Using Human Genome Data and Machine Learning.

IEEE transactions on bio-medical engineering Feb 4, 2019
UNLABELLED: Dengue has become one of the most important worldwide arthropod-borne diseases. Dengue phenotypes are based on laboratorial and clinical exams, which are known to be inaccurate.
Phenotype Prognosis Sensitivity and Specificity Brazil Case-Control Studies Humans Machine Learning Severe Dengue Polymorphism, Single Nucleotide Genotype Predictive Value of Tests Genome, Human
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Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs.

Journal of pain & palliative care pharmacotherapy Jan 31, 2019
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...
Health Care Costs Case-Control Studies Aged Cost of Illness Follow-Up Studies Adolescent Humans Young Adult Natural Language Processing United States Retrospective Studies Adult Analgesics, Opioid Longitudinal Studies Electronic Health Records Medicare Male Female Opioid-Related Disorders Middle Aged
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The feasibility of using robotic technology to quantify sensory, motor, and cognitive impairments associated with ALS.

Amyotrophic lateral sclerosis & frontotemporal degeneration Jan 27, 2019
OBJECTIVE: We used the KINARM robot to quantify impairments in cognitive and upper-limb sensorimotor performance in a cohort of people with amyotrophic lateral sclerosis (ALS). We sought to study the feasibility of using this technology for ALS resea...
Psychomotor Performance Task Performance and Analysis Upper Extremity Proprioception Case-Control Studies Cognitive Dysfunction Robotics Humans Amyotrophic Lateral Sclerosis Feasibility Studies Female Aged Male Middle Aged
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Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction.

Scientific reports Jan 24, 2019
Current approaches to predicting a cardiovascular disease (CVD) event rely on conventional risk factors and cross-sectional data. In this study, we applied machine learning and deep learning models to 10-year CVD event prediction by using longitudina...
Humans Longitudinal Studies Male Neural Networks, Computer Genetic Variation Female Cardiovascular Diseases Machine Learning Case-Control Studies Risk Factors Algorithms Adult Deep Learning Electronic Health Records Cross-Sectional Studies United States
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