AIMC Topic: Logistic Models

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A Cancer Paradox: Machine-Learning Backed Propensity-Score Analysis of Coronary Angiography Findings in Cardio-Oncology.

The Journal of invasive cardiology Jan 1, 2019
OBJECTIVES: Cancer has been proposed as a cardiovascular risk factor. We aimed to assess the cardiovascular risk profile and coronary angiography (CA) findings of cancer patients and compare them to those of patients without cancer.
Case-Control Studies Logistic Models Age Factors Coronary Angiography Male Risk Assessment Neoplasms Prevalence Multivariate Analysis Propensity Score Texas Cancer Care Facilities Coronary Artery Disease Reference Values Sex Factors Academic Medical Centers Humans Machine Learning Retrospective Studies Female Aged Aged, 80 and over
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Applying Artificial Intelligence to Identify Physiomarkers Predicting Severe Sepsis in the PICU.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Oct 1, 2018
OBJECTIVES: We used artificial intelligence to develop a novel algorithm using physiomarkers to predict the onset of severe sepsis in critically ill children.
Prospective Studies Female Male Case-Control Studies Humans Artificial Intelligence Machine Learning Organ Dysfunction Scores Respiratory Rate Logistic Models Sepsis Monitoring, Physiologic Predictive Value of Tests Adolescent Heart Rate Child Intensive Care Units, Pediatric
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Off-target predictions in CRISPR-Cas9 gene editing using deep learning.

Bioinformatics (Oxford, England) Sep 1, 2018
MOTIVATION: The prediction of off-target mutations in CRISPR-Cas9 is a hot topic due to its relevance to gene editing research. Existing prediction methods have been developed; however, most of them just calculated scores based on mismatches to the g...
Deep Learning Logistic Models Area Under Curve CRISPR-Cas Systems Algorithms Gene Editing
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Predicting Language Difficulties in Middle Childhood From Early Developmental Milestones: A Comparison of Traditional Regression and Machine Learning Techniques.

Journal of speech, language, and hearing research : JSLHR Aug 8, 2018
PURPOSE: The current study aimed to compare traditional logistic regression models with machine learning algorithms to investigate the predictive ability of (a) communication performance at 3 years old on language outcomes at 10 years old and (b) bro...
Child Language Algorithms Language Development Disorders Female Male Child, Preschool Humans Child Machine Learning Logistic Models Predictive Value of Tests Language Tests
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Incidence and location of positive surgical margin among open, laparoscopic and robot-assisted radical prostatectomy in prostate cancer patients: a single institutional analysis.

Japanese journal of clinical oncology Aug 1, 2018
OBJECTIVE: To evaluate the positive surgical margin rates and locations in radical prostatectomy among three surgical approaches, including open radical prostatectomy, laparoscopic radical prostatectomy and robot-assisted radical prostatectomy.
Prostatectomy Preoperative Care Margins of Excision Incidence Logistic Models Robotics Prostatic Neoplasms Prostate-Specific Antigen Laparoscopy Multivariate Analysis Propensity Score Risk Factors Aged Male Middle Aged Humans Retrospective Studies
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Applying Machine-Learning Techniques to Build Self-reported Depression Prediction Models.

Computers, informatics, nursing : CIN Jul 1, 2018
Mass Screening Self Report Datasets as Topic Male Middle Aged Depression Logistic Models Machine Learning Humans Female Aged Aged, 80 and over
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Automatic recognition of self-acknowledged limitations in clinical research literature.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2018
OBJECTIVE: To automatically recognize self-acknowledged limitations in clinical research publications to support efforts in improving research transparency.
Biomedical Research Logistic Models Support Vector Machine Natural Language Processing Publications PubMed Machine Learning
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Interactive medical word sense disambiguation through informed learning.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2018
OBJECTIVE: Medical word sense disambiguation (WSD) is challenging and often requires significant training with data labeled by domain experts. This work aims to develop an interactive learning algorithm that makes efficient use of expert's domain kno...
Medical Records Machine Learning Vocabulary Medicine Algorithms Logistic Models Natural Language Processing Medical Subject Headings
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[Comparison of machine learning method and logistic regression model in prediction of acute kidney injury in severely burned patients].

Zhonghua shao shang za zhi = Zhonghua shaoshang zazhi = Chinese journal of burns Jun 20, 2018
To build risk prediction models for acute kidney injury (AKI) in severely burned patients, and to compare the prediction performance of machine learning method and logistic regression model. The clinical data of 157 severely burned patients in Augu...
Fluid Therapy Sensitivity and Specificity Burns Humans Sepsis Organ Dysfunction Scores ROC Curve Machine Learning Explosions Logistic Models Acute Kidney Injury Hospitalization
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Effect of intraoperative mannitol administration on acute kidney injury after robot-assisted laparoscopic radical prostatectomy: A propensity score matching analysis.

Medicine Jun 1, 2018
Mannitol, an osmotic diuretic, has been used to prevent acute kidney injury (AKI). However, studies have found divergent effects of intraoperative mannitol administration on postoperative AKI. We therefore evaluated the effects of intraoperative mann...
Operative Time Robotics Prostatic Neoplasms Laparoscopy Postoperative Period Postoperative Complications Prostatectomy Humans Mannitol Logistic Models Acute Kidney Injury Socioeconomic Factors Risk Factors Body Mass Index Male
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