AIMC Topic: Predictive Value of Tests

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Developing neural network models for early detection of cardiac arrest in emergency department.

The American journal of emergency medicine Apr 7, 2019
BACKGROUND: Automated surveillance for cardiac arrests would be useful in overcrowded emergency departments. The purpose of this study is to develop and test artificial neural network (ANN) classifiers for early detection of patients at risk of cardi...
Logistic Models Predictive Value of Tests Emergency Service, Hospital Early Diagnosis Heart Arrest Humans Neural Networks, Computer Retrospective Studies Electronic Health Records Male Middle Aged ROC Curve Female Aged Adult
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Using a machine learning approach to predict outcome after surgery for degenerative cervical myelopathy.

PloS one Apr 4, 2019
Degenerative cervical myelopathy (DCM) is a spinal cord condition that results in progressive non-traumatic compression of the cervical spinal cord. Spine surgeons must consider a large quantity of information relating to disease presentation, imagin...
Intervertebral Disc Degeneration Decompression, Surgical Spinal Cord Diseases Middle Aged Postoperative Complications Comorbidity Treatment Outcome Predictive Value of Tests Humans Machine Learning Prospective Studies Female Male
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Predicting discharge placement after elective surgery for lumbar spinal stenosis using machine learning methods.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Apr 2, 2019
PURPOSE: An excessive amount of total hospitalization is caused by delays due to patients waiting to be placed in a rehabilitation facility or skilled nursing facility (RF/SNF). An accurate preoperative prediction of who would need a RF/SNF place aft...
Algorithms Spinal Stenosis Female Netherlands Aged Predictive Value of Tests Male Humans Quality Improvement Patient Transfer Postoperative Care Middle Aged Neural Networks, Computer Rehabilitation Centers Elective Surgical Procedures Machine Learning Skilled Nursing Facilities Lumbar Vertebrae Patient Discharge
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Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study.

The Lancet. Oncology Apr 2, 2019
BACKGROUND: The Response Assessment in Neuro-Oncology (RANO) criteria and requirements for a uniform protocol have been introduced to standardise assessment of MRI scans in both clinical trials and clinical practice. However, these criteria mainly re...
Humans Neural Networks, Computer Databases, Factual Retrospective Studies Female Time Factors Treatment Outcome Magnetic Resonance Imaging Multicenter Studies as Topic Randomized Controlled Trials as Topic Clinical Trials, Phase II as Topic Reproducibility of Results Brain Neoplasms Male Disease Progression Diagnosis, Computer-Assisted Germany Clinical Trials, Phase III as Topic Predictive Value of Tests Workflow Tumor Burden Image Interpretation, Computer-Assisted Automation
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Use of a molecular classifier to identify usual interstitial pneumonia in conventional transbronchial lung biopsy samples: a prospective validation study.

The Lancet. Respiratory medicine Apr 1, 2019
BACKGROUND: In the appropriate clinical setting, the diagnosis of idiopathic pulmonary fibrosis (IPF) requires a pattern of usual interstitial pneumonia to be present on high-resolution chest CT (HRCT) or surgical lung biopsy. A molecular usual inter...
Predictive Value of Tests Biopsy Prospective Studies Tomography, X-Ray Computed Female Reproducibility of Results Aged Humans Sensitivity and Specificity Lung Machine Learning Male Idiopathic Pulmonary Fibrosis Middle Aged Algorithms Diagnosis, Differential
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Simple Linear Support Vector Machine Classifier Can Distinguish Impaired Glucose Tolerance Versus Type 2 Diabetes Using a Reduced Set of CGM-Based Glycemic Variability Indices.

Journal of diabetes science and technology Mar 31, 2019
BACKGROUND: Many glycemic variability (GV) indices exist in the literature. In previous works, we demonstrated that a set of GV indices, extracted from continuous glucose monitoring (CGM) data, can distinguish between stages of diabetes progression. ...
Humans Algorithms Adult Male Middle Aged Female Reproducibility of Results Aged Health Status Indicators Data Interpretation, Statistical Blood Glucose Self-Monitoring Datasets as Topic Blood Glucose Glucose Intolerance Diabetes Mellitus, Type 2 Glycemic Control Support Vector Machine Diagnosis, Differential Predictive Value of Tests
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Use of machine learning in predicting clinical response to transcranial magnetic stimulation in comorbid posttraumatic stress disorder and major depression: A resting state electroencephalography study.

Journal of affective disorders Mar 30, 2019
BACKGROUND: Repetitive transcranial magnetic stimulation (TMS) is clinically effective for major depressive disorder (MDD) and investigational for other conditions including posttraumatic stress disorder (PTSD). Understanding the mechanisms of TMS ac...
Self Report Transcranial Magnetic Stimulation Rhode Island Stress Disorders, Post-Traumatic Treatment Outcome Support Vector Machine Predictive Value of Tests Electroencephalography Male Middle Aged Humans Depressive Disorder, Major Comorbidity Machine Learning Prefrontal Cortex Female Sensitivity and Specificity
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Combining many-objective radiomics and 3D convolutional neural network through evidential reasoning to predict lymph node metastasis in head and neck cancer.

Physics in medicine and biology Mar 29, 2019
Lymph node metastasis (LNM) is a significant prognostic factor in patients with head and neck cancer, and the ability to predict it accurately is essential to optimizing treatment. Positron emission tomography (PET) and computed tomography (CT) imagi...
Positron Emission Tomography Computed Tomography Imaging, Three-Dimensional Lymph Nodes Head and Neck Neoplasms Lymphatic Metastasis Predictive Value of Tests Humans Neural Networks, Computer
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Computed Tomography-Based Radiomic Features Could Potentially Predict Microsatellite Instability Status in Stage II Colorectal Cancer: A Preliminary Study.

Academic radiology Mar 28, 2019
RATIONALE AND OBJECTIVES: To investigate whether quantitative radiomics features extracted from computed tomography (CT) can predict microsatellite instability (MSI) status in an Asian cohort of patients with stage Ⅱ colorectal cancer (CRC).
Predictive Value of Tests Neoplasm Staging Microsatellite Instability Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Male Female Middle Aged Adult ROC Curve Colorectal Neoplasms
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Feature-weighted survival learning machine for COPD failure prediction.

Artificial intelligence in medicine Mar 28, 2019
Chronic obstructive pulmonary disease (COPD) yields a high rate of failures such as hospital readmission and death in the United States, Canada and worldwide. COPD failure imposes a significant social and economic burden on society, and predicting su...
Male Middle Aged Survival Analysis Severity of Illness Index Humans Canada Time Factors Proportional Hazards Models Risk Factors Machine Learning Age Factors Hospitalization ROC Curve Predictive Value of Tests Biomarkers Aged Sex Factors Prognosis Aged, 80 and over Patient Readmission Retrospective Studies Pulmonary Disease, Chronic Obstructive Electronic Health Records Female
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