AIMC Topic: Risk Factors

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[Risk factors for postoperative intestinal obstruction in patients undergoing robot-assisted laparoscopic radical prostatectomy].

Zhonghua yi xue za zhi Sep 15, 2020
To analyze the risk factors of postoperative intestinal obstruction (POI) in patients undergoing robot-assisted laparoscopic radical prostatectomy (RARP). The clinical data of 573 patients receiving RARP from January to December 2019 in Nanjing Dru...
Prostatic Neoplasms Humans Laparoscopy Retrospective Studies Intestinal Obstruction Risk Factors Prostatectomy Male Robotics
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Machine Learning With Feature Domains Elucidates Candidate Drivers of Hospital Readmission Following Spine Surgery in a Large Single-Center Patient Cohort.

Neurosurgery Sep 15, 2020
BACKGROUND: Unplanned hospital readmissions constitute a significant cost burden in healthcare. Identifying factors contributing to readmission risk presents opportunities for actionable change to reduce readmission rates.
Cohort Studies Patient Discharge Risk Factors Patient Readmission Humans Aged Spinal Diseases Machine Learning Adult Retrospective Studies Male Female Middle Aged
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Identification of Diabetes Risk Factors in Chronic Cardiovascular Patients.

Studies in health technology and informatics Sep 4, 2020
Specific predictive models for diabetes polyneuropathy based on screening methods, for example Nerve conduction studies (NCS, can reach up to AUC 65.8 - 84.7 % for the conditional diagnosis of DPN in primary care. Prediction methods that utilize data...
Humans Neural Networks, Computer Machine Learning Risk Factors Risk Assessment Diabetes Mellitus
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Assessment and prediction of restless leg syndrome (RLS) in patients with diabetes mellitus type II through artificial intelligence (AI).

Pakistan journal of pharmaceutical sciences Sep 1, 2020
This study aimed to diagnose the incidence of restless leg syndrome (RLS) in patients with diabetes mellitus (DM) type-2, thorough artificial intelligence based multilayer perceptron (MLP). 300 cases of diabetes mellitus type-2, of age between 18-80 ...
Predictive Value of Tests Pakistan Restless Legs Syndrome Young Adult Risk Assessment Humans Decision Support Techniques Adult Prevalence Neural Networks, Computer Female Cross-Sectional Studies Adolescent Artificial Intelligence Risk Factors Male Incidence Algorithms Aged Middle Aged Diabetes Mellitus, Type 2 Aged, 80 and over
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Gut Microbiota in T1DM-Onset Pediatric Patients: Machine-Learning Algorithms to Classify Microorganisms as Disease Linked.

The Journal of clinical endocrinology and metabolism Sep 1, 2020
AIMS: The purpose of this work is to find the gut microbial fingerprinting of pediatric patients with type 1 diabetes.
Diabetes Mellitus, Type 1 Machine Learning Algorithms Gastrointestinal Microbiome Female Adolescent Age of Onset Humans Risk Factors Metagenome Cohort Studies Male Child, Preschool Child Feces
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Can Machine-learning Algorithms Predict Early Revision TKA in the Danish Knee Arthroplasty Registry?

Clinical orthopaedics and related research Sep 1, 2020
BACKGROUND: Revision TKA is a serious adverse event with substantial consequences for the patient. As the demand for TKA rises, reducing the risk of revision TKA is becoming increasingly important. Predictive tools based on machine-learning algorithm...
Knee Injuries Body Weight Arthroplasty, Replacement, Knee Reoperation Preoperative Period Osteoarthritis, Knee Aged Adult Male Middle Aged Risk Assessment Postoperative Complications Age Factors Denmark Predictive Value of Tests Registries Humans Machine Learning Algorithms Female Risk Factors
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Leveraging Machine Learning to Identify Predictors of Receiving Psychosocial Treatment for Attention Deficit/Hyperactivity Disorder.

Administration and policy in mental health Sep 1, 2020
This study aimed to identify factors associated with receiving psychosocial treatment for ADHD in a nationally representative sample. Participants were 6630 youth with a parent-reported diagnosis of ADHD from the 2016-2017 National Survey of Children...
Humans Machine Learning Female Risk Factors Child ROC Curve Socioeconomic Factors Attention Deficit Disorder with Hyperactivity Patient Acceptance of Health Care Male Comorbidity Severity of Illness Index Adolescent Child, Preschool
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New artificial intelligence prediction model using serial prothrombin time international normalized ratio measurements in atrial fibrillation patients on vitamin K antagonists: GARFIELD-AF.

European heart journal. Cardiovascular pharmacotherapy Sep 1, 2020
AIMS: Most clinical risk stratification models are based on measurement at a single time-point rather than serial measurements. Artificial intelligence (AI) is able to predict one-dimensional outcomes from multi-dimensional datasets. Using data from ...
Time Factors Treatment Outcome Predictive Value of Tests Anticoagulants Blood Coagulation Risk Factors Aged Aged, 80 and over Male Risk Assessment Atrial Fibrillation Vitamin K Humans Hemorrhage Neural Networks, Computer Prothrombin Time Databases, Factual Drug Therapy, Computer-Assisted Prospective Studies International Normalized Ratio Female Drug Monitoring Reproducibility of Results Registries Stroke Administration, Oral
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Machine Learning for Predictive Modeling of 90-day Readmission, Major Medical Complication, and Discharge to a Facility in Patients Undergoing Long Segment Posterior Lumbar Spine Fusion.

Spine Aug 15, 2020
STUDY DESIGN: Retrospective case control study.
Machine Learning Databases, Factual Retrospective Studies Female Risk Factors Comorbidity Patient Discharge Case-Control Studies Patient Readmission Humans Postoperative Period Inpatients Spinal Fusion Aged Lumbar Vertebrae Adult Male Middle Aged Postoperative Complications
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Machine-learning algorithms for predicting results in liver transplantation: the problem of donor-recipient matching.

Current opinion in organ transplantation Aug 1, 2020
PURPOSE OF REVIEW: Classifiers based on artificial intelligence can be useful to solve decision problems related to the inclusion or removal of possible liver transplant candidates, and assisting in the heterogeneous field of donor-recipient (D-R) ma...
Graft Survival Liver Transplantation Tissue and Organ Procurement Donor Selection Neural Networks, Computer Machine Learning Prognosis Humans Risk Factors Tissue Donors
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