AIMC Topic: Humans

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Predicting persistent depressive symptoms in older adults: A machine learning approach to personalised mental healthcare.

Journal of affective disorders Dec 25, 2018
BACKGROUND: Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and suc...
Follow-Up Studies Age Factors Predictive Value of Tests Algorithms Decision Support Techniques Risk Assessment Delivery of Health Care Psychiatric Status Rating Scales Female Depression Logistic Models Aged Aged, 80 and over Male Humans Machine Learning
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Resting-state anticorrelated networks in Schizophrenia.

Psychiatry research. Neuroimaging Dec 25, 2018
Converging evidences from different lines of research suggest abnormalities in functional brain connectivity in schizophrenia. While positively correlated brain networks have been well researched, anticorrelated functional connectivity remains under ...
Temporal Lobe Humans Magnetic Resonance Imaging Brain Mapping Schizophrenia Adult Case-Control Studies Male Support Vector Machine Machine Learning Rest Gyrus Cinguli Brain Female Neural Pathways Thalamus
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Qualitative and Quantitative Analysis of Cathinones in Human Urine by SPE-GC-MS.

Fa yi xue za zhi Dec 25, 2018
OBJECTIVES: To propose an alternative solid phase extraction-gas chromatography-mass spectrometry （SPE-GC-MS） method for the sensitive determination of cathinones in human urine samples, plus methodological verification.
(1)
Alkaloids Solid Phase Extraction Gas Chromatography-Mass Spectrometry Humans Spectrum Analysis Reproducibility of Results Sensitivity and Specificity
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Decomposition Kinetics of Omethoate in Blood.

Fa yi xue za zhi Dec 25, 2018
OBJECTIVES: To study the decomposition kinetics of omethoate in blood.
Dimethoate Humans Chromatography, Liquid Tandem Mass Spectrometry Kinetics Spectrometry, Mass, Electrospray Ionization Chromatography, High Pressure Liquid
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Big Data Analysis and Machine Learning in Intensive Care Units.

Medicina intensiva Dec 24, 2018
Intensive care is an ideal environment for the use of Big Data Analysis (BDA) and Machine Learning (ML), due to the huge amount of information processed and stored in electronic format in relation to such care. These tools can improve our clinical re...
Information Dissemination Information Storage and Retrieval Intensive Care Units Electronic Health Records Data Analysis Big Data Databases, Factual Humans Retrospective Studies Data Anonymization Machine Learning Critical Care Randomized Controlled Trials as Topic Natural Language Processing
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Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss.

IEEE transactions on medical imaging Dec 24, 2018
Accurate detection of end-systolic (ES) and end-diastolic (ED) frames in an echocardiographic cine series can be difficult but necessary pre-processing step for the development of automatic systems to measure cardiac parameters. The detection task is...
Image Processing, Computer-Assisted Heart Myocardial Contraction Algorithms Echocardiography Deep Learning Humans
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Deep Convolutional Neural Networks for Feature-Less Automatic Classification of Independent Components in Multi-Channel Electrophysiological Brain Recordings.

IEEE transactions on bio-medical engineering Dec 24, 2018
OBJECTIVE: Interpretation of the electroencephalographic (EEG) and magnetoencephalographic (MEG) signals requires off-line artifacts removal. Since artifacts share frequencies with brain activity, filtering is insufficient. Blind source separation, m...
Humans Electroencephalography Signal Processing, Computer-Assisted Artifacts Magnetoencephalography Algorithms Brain Deep Learning
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Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model.

HPB : the official journal of the International Hepato Pancreato Biliary Association Dec 24, 2018
BACKGROUND: To predict the risk and severity of acute respiratory distress syndrome (ARDS) following severe acute pancreatitis (SAP) by artificial neural networks (ANNs) model.
Neural Networks, Computer Decision Support Techniques Prognosis Female Humans Male Middle Aged Risk Assessment Severity of Illness Index Reproducibility of Results Risk Factors Adult Respiratory Distress Syndrome Predictive Value of Tests Pancreatitis
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iRNA-PseKNC(2methyl): Identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components.

Journal of theoretical biology Dec 24, 2018
The 2'-O-methylation transferase is involved in the process of 2'-O-methylation. In catalytic processes, the 2-hydroxy group of the ribose moiety of a nucleotide accept a methyl group. This methylation process is a post-transcriptional modification, ...
Algorithms Deep Learning Computational Biology Humans Binding Sites Neural Networks, Computer RNA Machine Learning Methylation
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Picomolar detection of retinol binding protein 4 for early management of type II diabetes.

Biosensors & bioelectronics Dec 24, 2018
Type (II) diabetes is one of the major threats to mankind as it causes insulin resistance in human body and Retinol Binding Protein 4 (RBP4) is currently considered as a potential biomarker for early management of this disease. Hence a low-level dete...
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Diabetes Mellitus, Type 2 Biosensing Techniques Insulin Resistance Retinol-Binding Proteins, Plasma Electrodes Humans Glutaral Blood Glucose Insulin
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