AIMC Topic: Recurrence

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Preprocedure Application of Machine Learning and Mechanistic Simulations Predicts Likelihood of Paroxysmal Atrial Fibrillation Recurrence Following Pulmonary Vein Isolation.

Circulation. Arrhythmia and electrophysiology Jun 14, 2020
BACKGROUND: Pulmonary vein isolation (PVI) is an effective treatment strategy for patients with atrial fibrillation (AF), but many experience AF recurrence and require repeat ablation procedures. The goal of this study was to develop and evaluate a m...
Diagnosis, Computer-Assisted Treatment Outcome Contrast Media Humans Magnetic Resonance Imaging Machine Learning Action Potentials Retrospective Studies Risk Factors Female Aged Reproducibility of Results Male Middle Aged Organometallic Compounds Risk Assessment Recurrence Predictive Value of Tests Models, Cardiovascular Patient-Specific Modeling Atrial Fibrillation Pulmonary Veins Heart Rate Meglumine Catheter Ablation Proof of Concept Study
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Retrospective Cohort Analysis from a High-Volume Center of Prognostic Factors Affecting Biochemical Relapse in Patients with Encapsulated, Margin-Negative, Isolated Seminal Vesicle Invasion After Robot-Assisted Laparoscopic Prostatectomy: A Novel Study.

Journal of endourology Mar 10, 2020
Specimen pathology findings collectively impact the long-term outcomes of robot-assisted laparoscopic prostatectomy. Since seminal vesicle invasion (SVI) is an important independent predictor of biochemical recurrence (BCR), this study was designed ...
Laparoscopy Neoplasm Recurrence, Local Male Prostatectomy Cohort Studies Recurrence Humans Robotics Seminal Vesicles Prognosis Prostatic Neoplasms Retrospective Studies Prostate-Specific Antigen
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Extreme Gradient Boosting Model Has a Better Performance in Predicting the Risk of 90-Day Readmissions in Patients with Ischaemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Oct 16, 2019
OBJECT: Ischemic stroke readmission within 90 days of hospital discharge is an important quality of care metric. The readmission rates of ischemic stroke patients are usually higher than those of patients with other chronic diseases. Our aim was to i...
Humans Machine Learning Decision Support Techniques Retrospective Studies Female Risk Assessment Time Factors Predictive Value of Tests Stroke Patient Readmission Reproducibility of Results Risk Factors Aged Male Middle Aged Brain Ischemia Recurrence
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Automatic detection of epileptic seizure based on approximate entropy, recurrence quantification analysis and convolutional neural networks.

Artificial intelligence in medicine Sep 7, 2019
Epilepsy is the most common neurological disorder in humans. Electroencephalogram is a prevalent tool for diagnosing the epileptic seizure activity in clinical, which provides valuable information for understanding the physiological mechanisms behind...
Epilepsy Seizures Automation Recurrence Entropy Humans Neural Networks, Computer Algorithms Databases, Factual Sensitivity and Specificity Electroencephalography
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Prediction of local relapse and distant metastasis in patients with definitive chemoradiotherapy-treated cervical cancer by deep learning from [F]-fluorodeoxyglucose positron emission tomography/computed tomography.

European radiology May 27, 2019
BACKGROUND: We designed a deep learning model for assessing F-FDG PET/CT for early prediction of local and distant failures for patients with locally advanced cervical cancer.
Humans Prognosis Retrospective Studies Female Aged Aged, 80 and over Adult Fluorodeoxyglucose F18 Treatment Outcome Chemoradiotherapy Sensitivity and Specificity Cervix Uteri Recurrence Uterine Cervical Neoplasms Positron Emission Tomography Computed Tomography Middle Aged Neoplasm Recurrence, Local Deep Learning Radiopharmaceuticals Cohort Studies
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Time series analysis of human brucellosis in mainland China by using Elman and Jordan recurrent neural networks.

BMC infectious diseases May 14, 2019
BACKGROUND: Establishing epidemiological models and conducting predictions seems to be useful for the prevention and control of human brucellosis. Autoregressive integrated moving average (ARIMA) models can capture the long-term trends and the period...
Jordan Humans Neural Networks, Computer Models, Statistical Seasons Recurrence China Incidence Brucellosis
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Deep learning-based survival prediction of oral cancer patients.

Scientific reports May 6, 2019
The Cox proportional hazards model commonly used to evaluate prognostic variables in survival of cancer patients may be too simplistic to properly predict a cancer patient's outcome since it assumes that the outcome is a linear combination of covaria...
Mouth Neoplasms Survival Analysis Proportional Hazards Models Recurrence Carcinoma, Squamous Cell Humans Aged Prognosis Male Retrospective Studies Middle Aged Female Deep Learning
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Comparisons of efficacy, safety, and recurrence risk factors of paroxysmal and persistent atrial fibrillation catheter ablation using robotic magnetic navigation system.

Clinical cardiology Mar 15, 2019
BACKGROUND: No data exist on comparisons of efficacy, safety, and recurrence risk factors of paroxysmal and persistent atrial fibrillation (AF) ablation using robotic magnetic navigation system (MNS), respectively.
Catheter Ablation Recurrence Pulmonary Veins Humans Surgery, Computer-Assisted Prospective Studies Young Adult Adolescent Heart Conduction System Tomography, X-Ray Computed Adult Treatment Outcome Atrial Fibrillation Female Male Follow-Up Studies Heart Atria Risk Factors Robotics Echocardiography Heart Rate Aged Equipment Design Middle Aged
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Machine learning model to predict recurrent ulcer bleeding in patients with history of idiopathic gastroduodenal ulcer bleeding.

Alimentary pharmacology & therapeutics Feb 13, 2019
BACKGROUND: Patients with a history of Helicobacter pylori-negative idiopathic bleeding ulcers have an increased risk of recurring ulcer complications.
Gastrointestinal Hemorrhage Duodenal Ulcer Recurrence Stomach Ulcer Middle Aged Cohort Studies Follow-Up Studies Helicobacter Infections Helicobacter pylori Humans Retrospective Studies Machine Learning Female Prospective Studies Aged Adult Male
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Using neuroimaging to predict relapse in stimulant dependence: A comparison of linear and machine learning models.

NeuroImage. Clinical Jan 11, 2019
OBJECTIVE: Relapse rates are consistently high for stimulant user disorders. In order to obtain prognostic information about individuals in treatment, machine learning models have been applied to neuroimaging and clinical data. Yet few efforts have b...
Neuroimaging Depressive Disorder, Major Recurrence Humans ROC Curve Machine Learning Logistic Models Female Longitudinal Studies Adult Methamphetamine Male
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