AIMC Topic: Clinical Decision Rules

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Machine learning to predict early recurrence after oesophageal cancer surgery.

The British journal of surgery Jan 30, 2020
BACKGROUND: Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20-30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This s...
Female Aged Aged, 80 and over Adult Male Humans Machine Learning Area Under Curve Neoplasm Recurrence, Local Esophagectomy Esophageal Neoplasms Clinical Decision Rules Middle Aged Risk Assessment ROC Curve Adenocarcinoma
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Comparing different supervised machine learning algorithms for disease prediction.

BMC medical informatics and decision making Dec 21, 2019
BACKGROUND: Supervised machine learning algorithms have been a dominant method in the data mining field. Disease prediction using health data has recently shown a potential application area for these methods. This study ai7ms to identify the key tren...
Humans Risk Factors Support Vector Machine Bayes Theorem Machine Learning Algorithms Data Mining Clinical Decision Rules
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Prediction of lithium response using clinical data.

Acta psychiatrica Scandinavica Nov 22, 2019
OBJECTIVE: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical ma...
Machine Learning Female Risk Factors Adult Male Humans Age of Onset Sleep Initiation and Maintenance Disorders Clinical Decision Rules Middle Aged Disease Progression Bipolar Disorder Lithium Compounds Antimanic Agents ROC Curve Treatment Outcome Area Under Curve
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Machine Learning-Based Prediction Models for 30-Day Readmission after Hospitalization for Chronic Obstructive Pulmonary Disease.

COPD Nov 11, 2019
While machine learning approaches can enhance prediction ability, little is known about their ability to predict 30-day readmission after hospitalization for Chronic Obstructive Pulmonary Disease (COPD). We identified patients aged ≥40 years with unp...
Pulmonary Disease, Chronic Obstructive Male Middle Aged Risk Assessment Logistic Models Hospitalization Aged Aged, 80 and over Adult Japan Patient Readmission Clinical Decision Rules Databases, Factual Prognosis Female Humans Machine Learning
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Prediction of good neurological recovery after out-of-hospital cardiac arrest: A machine learning analysis.

Resuscitation Jul 27, 2019
BACKGROUND: This study aimed to train, validate and compare predictive models that use machine learning analysis for good neurological recovery in OHCA patients.
Humans Machine Learning Recovery of Function Heart Diseases Nervous System Diseases Prognosis Reproducibility of Results Cardiopulmonary Resuscitation Out-of-Hospital Cardiac Arrest Clinical Decision Rules
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Optimizing neural networks for medical data sets: A case study on neonatal apnea prediction.

Artificial intelligence in medicine Jul 25, 2019
OBJECTIVE: The neonatal period of a child is considered the most crucial phase of its physical development and future health. As per the World Health Organization, India has the highest number of pre-term births [1], with over 3.5 million babies born...
Algorithms Infant, Newborn Infant, Extremely Premature Deep Learning India Humans Neural Networks, Computer Clinical Decision Rules Apnea Support Vector Machine Decision Trees Birth Weight Heart Rate Datasets as Topic Infant, Premature Gestational Age Intensive Care Units, Neonatal
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Predicting asthma attacks in primary care: protocol for developing a machine learning-based prediction model.

BMJ open Jul 9, 2019
INTRODUCTION: Asthma is a long-term condition with rapid onset worsening of symptoms ('attacks') which can be unpredictable and may prove fatal. Models predicting asthma attacks require high sensitivity to minimise mortality risk, and high specificit...
Support Vector Machine Emergency Service, Hospital Bayes Theorem Symptom Flare Up Scotland Clinical Decision Rules Machine Learning Hospitalization Asthma Risk Assessment Primary Health Care Humans
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Comparison of Machine Learning Methods With National Cardiovascular Data Registry Models for Prediction of Risk of Bleeding After Percutaneous Coronary Intervention.

JAMA network open Jul 3, 2019
IMPORTANCE: Better prediction of major bleeding after percutaneous coronary intervention (PCI) may improve clinical decisions aimed to reduce bleeding risk. Machine learning techniques, bolstered by better selection of variables, hold promise for enh...
Coronary Artery Disease Risk Adjustment Comparative Effectiveness Research Clinical Decision Rules Models, Statistical Postoperative Hemorrhage Registries Percutaneous Coronary Intervention Aged Male Risk Assessment United States Humans Machine Learning Female
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Machine learning methods for developing precision treatment rules with observational data.

Behaviour research and therapy May 28, 2019
Clinical trials have identified a variety of predictor variables for use in precision treatment protocols, ranging from clinical biomarkers and symptom profiles to self-report measures of various sorts. Although such variables are informative collect...
Suicide, Attempted Suicide Prevention Decision Support Systems, Clinical Observational Studies as Topic Humans Machine Learning Databases, Factual Precision Medicine Information Storage and Retrieval Clinical Decision Rules
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A novel machine-learning-based infection screening system via 2013-2017 seasonal influenza patients' vital signs as training datasets.

The Journal of infection Feb 22, 2019
Male Middle Aged Adolescent Child Aged, 80 and over Influenza, Human Vital Signs Clinical Decision Rules Young Adult Mass Screening Adult Predictive Value of Tests Sensitivity and Specificity Humans Machine Learning Female Aged
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