AIMC Topic: Clinical Decision Rules

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Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.

JAMA network open Jun 1, 2020
IMPORTANCE: Despite the high prevalence and potential outcomes of major depressive disorder, whether and how patients will respond to antidepressant medications is not easily predicted.
Humans Machine Learning Algorithms Prospective Studies Treatment Outcome Electroencephalography Antidepressive Agents Citalopram Clinical Decision Rules Sertraline Venlafaxine Hydrochloride Prognosis Female Adult Male Middle Aged Depressive Disorder, Major
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Pulmonary Embolism in Acute Asthma Exacerbation: Clinical Characteristics, Prediction Model and Hospital Outcomes.

Lung May 18, 2020
PURPOSE: Little is known about the characteristics and impact of acute pulmonary embolism (PE) during episodes of asthma exacerbation. We aimed to characterize patients diagnosed with acute PE in the setting of asthma exacerbation, develop a predicti...
Adult Asthma Male Middle Aged Disease Progression Comorbidity Case-Control Studies Humans Machine Learning Intensive Care Units Female Aged Hospitals, University Heart Rate Natriuretic Peptide, Brain Fibrin Fibrinogen Degradation Products Computed Tomography Angiography Clinical Decision Rules Length of Stay Body Mass Index Oxygen International Normalized Ratio Pulmonary Embolism Creatinine
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Natural Language Processing Improves Detection of Nonsevere Hypoglycemia in Medical Records Versus Coding Alone in Patients With Type 2 Diabetes but Does Not Improve Prediction of Severe Hypoglycemia Events: An Analysis Using the Electronic Medical Record in a Large Health System.

Diabetes care May 15, 2020
OBJECTIVE: To determine if natural language processing (NLP) improves detection of nonsevere hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of fu...
Community Health Planning Clinical Decision Rules United States Predictive Value of Tests Natural Language Processing Hypoglycemia Information Storage and Retrieval International Classification of Diseases Humans Algorithms Electronic Health Records Female Aged Aged, 80 and over Young Adult Adult Male Middle Aged Severity of Illness Index Diabetes Mellitus, Type 2
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Development and validation of machine learning prediction model based on computed tomography angiography-derived hemodynamics for rupture status of intracranial aneurysms: a Chinese multicenter study.

European radiology Apr 29, 2020
OBJECTIVES: To build models based on conventional logistic regression (LR) and machine learning (ML) algorithms combining clinical, morphological, and hemodynamic information to predict individual rupture status of unruptured intracranial aneurysms (...
Support Vector Machine Area Under Curve Computed Tomography Angiography Cerebral Angiography Aneurysm, Ruptured Intracranial Aneurysm Male Middle Aged Hemodynamics China Adolescent Logistic Models Clinical Decision Rules Humans Neural Networks, Computer Machine Learning Computer Simulation Retrospective Studies Tomography, X-Ray Computed Female Aged Aged, 80 and over Young Adult Adult
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Development and Validation of Machine Learning Algorithms for Predicting Adverse Events After Surgery for Lumbar Degenerative Spondylolisthesis.

World neurosurgery Apr 25, 2020
BACKGROUND: Preoperative prognostication of adverse events (AEs) for patients undergoing surgery for lumbar degenerative spondylolisthesis (LDS) can improve risk stratification and help guide the surgical decision-making process. The aim of this stud...
Middle Aged Postoperative Complications Adolescent Logistic Models Age Factors Decision Making Functional Status Risk Factors Transplantation, Autologous Humans Neurosurgical Procedures Aged Bone Transplantation Spinal Fusion Ilium Machine Learning Lumbar Vertebrae Aged, 80 and over Serum Albumin Alkaline Phosphatase Algorithms Young Adult Sex Factors Spondylolisthesis Prognosis Adult Clinical Decision Rules Female Male
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Early short-term prediction of emergency department length of stay using natural language processing for low-acuity outpatients.

The American journal of emergency medicine Mar 10, 2020
BACKGROUND: Low-acuity outpatients constitute the majority of emergency department (ED) patients, and these patients often experience an unpredictable length of stay (LOS). Effective LOS prediction might improve the quality of ED care and reduce ED c...
Clinical Decision Rules Natural Language Processing Emergency Service, Hospital Patient Acuity Vital Signs Outpatients Crowding Aged Adult Male Middle Aged Length of Stay Taiwan Humans Retrospective Studies Female
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Development and Evaluation of a Machine Learning Prediction Model for Flap Failure in Microvascular Breast Reconstruction.

Annals of surgical oncology Mar 9, 2020
BACKGROUND: Despite high success rates, flap failure remains an inherent risk in microvascular breast reconstruction. Identifying patients who are at high risk for flap failure would enable us to recommend alternative reconstructive techniques. Howev...
Humans Artificial Intelligence Clinical Decision Rules Machine Learning Breast Neoplasms Middle Aged Prognosis Graft Survival Retrospective Studies Decision Trees Female Surgical Flaps Risk Factors Mammaplasty Aged Microcirculation Adult
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Prehospital triage of acute aortic syndrome using a machine learning algorithm.

The British journal of surgery Feb 11, 2020
BACKGROUND: Acute aortic syndrome (AAS) comprises a complex and potentially fatal group of conditions requiring emergency specialist management. The aim of this study was to build a prediction algorithm to assist prehospital triage of AAS.
Syndrome Aortic Diseases Clinical Decision Rules Middle Aged Hospital Mortality Humans Logistic Models Machine Learning Prospective Studies Emergency Medical Services Algorithms Prognosis Triage Female Acute Disease Reproducibility of Results Aged Male
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Development and Validation of a Machine Learning Individualized Treatment Rule in First-Episode Schizophrenia.

JAMA network open Feb 5, 2020
IMPORTANCE: Little guidance exists to date on how to select antipsychotic medications for patients with first-episode schizophrenia.
Schizophrenia Young Adult Humans Antipsychotic Agents Adult Machine Learning Clinical Decision Rules Male Precision Medicine Middle Aged Prognosis Treatment Outcome Models, Statistical Retrospective Studies Female
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Using artificial intelligence (AI) to predict postoperative surgical site infection: A retrospective cohort of 4046 posterior spinal fusions.

Clinical neurology and neurosurgery Feb 3, 2020
OBJECTIVES: Machine Learning and Artificial Intelligence (AI) are rapidly growing in capability and increasingly applied to model outcomes and complications within medicine. In spinal surgery, post-operative surgical site infections (SSIs) are a rare...
Male Middle Aged Comorbidity Deep Learning Cohort Studies ROC Curve Area Under Curve Spinal Fusion Surgical Wound Infection Clinical Decision Rules Humans Neural Networks, Computer Artificial Intelligence Machine Learning Retrospective Studies Female
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