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Applying Machine Learning Across Sites: External Validation of a Surgical Site Infection Detection Algorithm.

Journal of the American College of Surgeons Apr 5, 2021
BACKGROUND: Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. To...
Datasets as Topic Medical Audit Humans Machine Learning Electronic Health Records Female Risk Factors Aged Male Adult Middle Aged Hospitals Surgical Wound Infection Quality Improvement
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Individualized embryo selection strategy developed by stacking machine learning model for better in vitro fertilization outcomes: an application study.

Reproductive biology and endocrinology : RB&E Apr 5, 2021
BACKGROUND: To minimize the rate of in vitro fertilization (IVF)- associated multiple-embryo gestation, significant efforts have been made. Previous studies related to machine learning in IVF mainly focused on selecting the top-quality embryos to imp...
Pregnancy Rate Fertilization in Vitro Treatment Outcome Models, Statistical Embryo, Mammalian Infertility Single Embryo Transfer Prognosis Pregnancy Female Adult Male Humans Artificial Intelligence Machine Learning Computer Simulation
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Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.

Auris, nasus, larynx Apr 4, 2021
OBJECTIVE: We examined whether artificial intelligence (AI) used with the novel digital image enhancement system modalities (CLARA+CHROMA, SPECTRA A, and SPECTRA B) could distinguish the cholesteatoma matrix, cholesteatoma debris, and normal middle e...
Middle Aged Adolescent Diagnosis, Differential Aged Surgery, Computer-Assisted Ear, Middle Humans Aged, 80 and over Cholesteatoma, Middle Ear Image Enhancement Neural Networks, Computer Adult Female Endoscopy Male
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Prediction of Distal Aortic Enlargement after Proximal Repair of Aortic Dissection Using Machine Learning.

Annals of vascular surgery Apr 3, 2021
OBJECTIVES: This study aimed to construct a risk prediction model for distal aortic enlargement in patients with type B aortic dissection (TBAD) treated with proximal thoracic endovascular aortic repair (TEVAR).
Aortic Rupture Humans Neural Networks, Computer Decision Support Techniques Risk Assessment Time Factors Aged Aortic Aneurysm, Thoracic Treatment Outcome Retrospective Studies Adult Blood Vessel Prosthesis Implantation Support Vector Machine Electronic Health Records Dilatation, Pathologic Endovascular Procedures Aortic Dissection Clinical Decision-Making Male Vascular Remodeling Female Middle Aged Aorta Risk Factors
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Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage.

Journal of the American College of Radiology : JACR Apr 3, 2021
OBJECTIVE: To determine the institutional diagnostic accuracy of an artificial intelligence (AI) decision support systems (DSS), Aidoc, in diagnosing intracranial hemorrhage (ICH) on noncontrast head CTs and to assess the potential generalizability o...
Humans Intracranial Hemorrhages Aged, 80 and over Adult Male Middle Aged Deep Learning Artificial Intelligence Algorithms Retrospective Studies Female Aged
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Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.

World neurosurgery Apr 2, 2021
OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distin...
Brain Neoplasms Male Middle Aged Adolescent Cohort Studies Female Reproducibility of Results Young Adult Adult Sensitivity and Specificity Predictive Value of Tests Area Under Curve Mutation Histones Child ROC Curve Image Processing, Computer-Assisted Glioma Magnetic Resonance Imaging Humans Machine Learning Algorithms
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Prediction of eating disorder treatment response trajectories via machine learning does not improve performance versus a simpler regression approach.

The International journal of eating disorders Apr 2, 2021
OBJECTIVE: Patterns of response to eating disorder (ED) treatment are heterogeneous. Advance knowledge of a patient's expected course may inform precision medicine for ED treatment. This study explored the feasibility of applying machine learning to ...
Humans Machine Learning Female Hospitalization Adult Adolescent ROC Curve Logistic Models Feeding and Eating Disorders
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Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease.

Diabetologia Apr 2, 2021
AIM: Predicting progression in diabetic kidney disease (DKD) is critical to improving outcomes. We sought to develop/validate a machine-learned, prognostic risk score (KidneyIntelX™) combining electronic health records (EHR) and biomarkers.
Female Risk Factors Aged Aged, 80 and over Diabetic Nephropathies Young Adult Adult United States Humans Male Glomerular Filtration Rate Machine Learning Middle Aged Kidney Function Tests Biomarkers Disease Progression Predictive Value of Tests Prognosis Cohort Studies Electronic Health Records
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Development and Assessment of an Artificial Intelligence-Based Tool for Skin Condition Diagnosis by Primary Care Physicians and Nurse Practitioners in Teledermatology Practices.

JAMA network open Apr 1, 2021
IMPORTANCE: Most dermatologic cases are initially evaluated by nondermatologists such as primary care physicians (PCPs) or nurse practitioners (NPs).
Dermatology Humans Male Artificial Intelligence Referral and Consultation Middle Aged Female Physicians, Primary Care Diagnosis, Computer-Assisted Adult Nurse Practitioners Skin Diseases Telemedicine
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Development and Validation of a Machine Learning Model to Estimate Bacterial Sepsis Among Immunocompromised Recipients of Stem Cell Transplant.

JAMA network open Apr 1, 2021
IMPORTANCE: Sepsis disproportionately affects recipients of allogeneic hematopoietic cell transplant (allo-HCT), and timely detection is crucial. However, the atypical presentation of sepsis within this population makes detection challenging, and exi...
Hematopoietic Stem Cell Transplantation Random Allocation Immunocompetence Male Middle Aged Humans Risk Assessment Machine Learning Sepsis Decision Support Techniques ROC Curve Retrospective Studies Female Adult
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