AIMC Topic: Sensitivity and Specificity

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Melanoma lesion detection and segmentation using deep region based convolutional neural network and fuzzy C-means clustering.

International journal of medical informatics Jan 18, 2019
OBJECTIVE: Melanoma is a dangerous form of the skin cancer responsible for thousands of deaths every year. Early detection of melanoma is possible through visual inspection of pigmented lesions over the skin, treated with simple excision of the cance...
Dermoscopy Sensitivity and Specificity Fuzzy Logic Cluster Analysis Humans Neural Networks, Computer Melanoma Skin Neoplasms
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Development and Evaluation of a Machine Learning Model for the Early Identification of Patients at Risk for Sepsis.

Annals of emergency medicine Jan 17, 2019
STUDY OBJECTIVE: The Third International Consensus Definitions (Sepsis-3) Task Force recommended the use of the quick Sequential [Sepsis-related] Organ Failure Assessment (qSOFA) score to screen patients for sepsis outside of the ICU. However, subseq...
Male Middle Aged Severity of Illness Index Sepsis Organ Dysfunction Scores Hospitals, Urban Early Diagnosis Lactic Acid Retrospective Studies Female Aged Sensitivity and Specificity Humans Machine Learning
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Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers' Health Examination Data.

International journal of environmental research and public health Jan 16, 2019
We aimed to use deep learning to detect tuberculosis in chest radiographs in annual workers' health examination data and compare the performances of convolutional neural networks (CNNs) based on images only (I-CNN) and CNNs including demographic vari...
Humans Tuberculosis, Pulmonary Occupational Health Demography Physical Examination Middle Aged Female Deep Learning Adult ROC Curve Sensitivity and Specificity Radiography Male
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Rapid detection of internalizing diagnosis in young children enabled by wearable sensors and machine learning.

PloS one Jan 16, 2019
There is a critical need for fast, inexpensive, objective, and accurate screening tools for childhood psychopathology. Perhaps most compelling is in the case of internalizing disorders, like anxiety and depression, where unobservable symptoms cause c...
Supervised Machine Learning Affect Psychopathology Psychology, Child ROC Curve Logistic Models Models, Statistical Signal Processing, Computer-Assisted Depression Wearable Electronic Devices Child, Preschool Child Sensitivity and Specificity Male Humans Anxiety Female
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Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error.

Systematic reviews Jan 15, 2019
BACKGROUND: Here, we outline a method of applying existing machine learning (ML) approaches to aid citation screening in an on-going broad and shallow systematic review of preclinical animal studies. The aim is to achieve a high-performing algorithm ...
Depressive Disorder Bibliometrics Systematic Reviews as Topic Workload Models, Animal Algorithms Sensitivity and Specificity Animals Humans Machine Learning
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Automated identification for autism severity level: EEG analysis using empirical mode decomposition and second order difference plot.

Behavioural brain research Jan 11, 2019
BACKGROUND: Previous automated EEG-based diagnosis of autism spectrum disorders (ASD) using various nonlinear EEG analysis methods were limited to distinguish only children with ASD from those normally developed without approaching their autistic fea...
Humans Neural Networks, Computer Autism Spectrum Disorder Child Electroencephalography Signal Processing, Computer-Assisted Autistic Disorder Behavior Female Sensitivity and Specificity Male Child, Preschool
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Role of interleukin-3 as a prognostic marker in septic patients.

Revista Brasileira de terapia intensiva Jan 10, 2019
OBJECTIVE: To evaluate the accuracy of IL-3 to predict the outcome of septic patients.
Sensitivity and Specificity Male Female Humans Middle Aged Cohort Studies Shock, Septic Reproducibility of Results Prospective Studies Sepsis Hospital Mortality Predictive Value of Tests Aged Prognosis Interleukin-3 Adult Intensive Care Units
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Using Machine Learning to Identify Change in Surgical Decision Making in Current Use of Damage Control Laparotomy.

Journal of the American College of Surgeons Jan 9, 2019
BACKGROUND: In an earlier study, we reported the successful reduction in the use of damage control laparotomy (DCL); however, no change in the relative frequencies of specific indications was observed. In this study, we aimed to use machine learning ...
Sensitivity and Specificity Male Middle Aged Trauma Severity Indices Clinical Decision-Making Quality Improvement Humans Blood Transfusion Laparotomy Female Machine Learning Blood Pressure Abdominal Injuries Young Adult Algorithms Patient Selection Adult Retrospective Studies
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Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients.

PloS one Jan 9, 2019
BACKGROUND: Patient with acute coronary syndrome benefits from early revascularization. However, methods for the selection of patients who require urgent revascularization from a variety of patients visiting the emergency room with chest symptoms is ...
Sensitivity and Specificity Diagnosis, Computer-Assisted Time Factors Electrocardiography Humans Chest Pain Neural Networks, Computer Acute Coronary Syndrome Prognosis Datasets as Topic Myocardial Revascularization Decision Making, Computer-Assisted Diagnosis, Differential Predictive Value of Tests Emergency Service, Hospital Patient Selection
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Alternative Diagnosis of Epilepsy in Children Without Epileptiform Discharges Using Deep Convolutional Neural Networks.

International journal of neural systems Jan 8, 2019
Numerous nonepileptic paroxysmal events, such as syncope and psychogenic nonepileptic seizures, may imitate seizures and impede diagnosis. Misdiagnosis can lead to mistreatment, affecting patients' lives considerably. Electroencephalography is common...
Syncope Deep Learning Humans Pilot Projects Tourette Syndrome Child Female Electroencephalography Sensitivity and Specificity Epilepsy Male
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