AIMC Topic: Female

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Quantification of Fluid Resolution and Visual Acuity Gain in Patients With Diabetic Macular Edema Using Deep Learning: A Post Hoc Analysis of a Randomized Clinical Trial.

JAMA ophthalmology Sep 1, 2020
IMPORTANCE: Large amounts of optical coherence tomographic (OCT) data of diabetic macular edema (DME) are acquired, but many morphologic features have yet to be identified and quantified.
Follow-Up Studies Aged Visual Acuity Humans Male Macular Edema Recombinant Fusion Proteins Diabetic Retinopathy Vascular Endothelial Growth Factor A Middle Aged Algorithms Ranibizumab Intravitreal Injections Deep Learning Retrospective Studies Receptors, Vascular Endothelial Growth Factor Angiogenesis Inhibitors Female Subretinal Fluid
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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.
Cohort Studies Child, Preschool Humans Child Gastrointestinal Microbiome Machine Learning Feces Age of Onset Diabetes Mellitus, Type 1 Metagenome Algorithms Female Risk Factors Male Adolescent
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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...
Preoperative Period Osteoarthritis, Knee Knee Injuries Predictive Value of Tests Algorithms Registries Female Middle Aged Body Weight Risk Factors Risk Assessment Arthroplasty, Replacement, Knee Aged Postoperative Complications Reoperation Adult Age Factors Humans Male Denmark Machine Learning
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Dynamic impact of transfusion ratios on outcomes in severely injured patients: Targeted machine learning analysis of the Pragmatic, Randomized Optimal Platelet and Plasma Ratios randomized clinical trial.

The journal of trauma and acute care surgery Sep 1, 2020
BACKGROUND: Massive transfusion protocols to treat postinjury hemorrhage are based on predefined blood product transfusion ratios followed by goal-directed transfusion based on patient's clinical evolution. However, it remains unclear how these trans...
Humans Machine Learning Female Male Hemorrhage Erythrocytes Blood Platelets Plasma Intention to Treat Analysis Blood Component Transfusion Wounds and Injuries Hemostasis North America Trauma Centers
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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...
Male Comorbidity Severity of Illness Index Adolescent Humans Child Child, Preschool Machine Learning ROC Curve Female Socioeconomic Factors Risk Factors Attention Deficit Disorder with Hyperactivity Patient Acceptance of Health Care
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Deep learning assisted differentiation of hepatocellular carcinoma from focal liver lesions: choice of four-phase and three-phase CT imaging protocol.

Abdominal radiology (New York) Sep 1, 2020
PURPOSE: To evaluate whether a three-phase dynamic contrast-enhanced CT protocol, when combined with a deep learning model, has similar accuracy in differentiating hepatocellular carcinoma (HCC) from other focal liver lesions (FLLs) compared with a f...
Carcinoma, Hepatocellular Contrast Media Tomography, Spiral Computed Adult Male Middle Aged Deep Learning Liver Neoplasms Retrospective Studies Humans Female Aged Aged, 80 and over Young Adult
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Augmenting Interpretation of Chest Radiographs With Deep Learning Probability Maps.

Journal of thoracic imaging Sep 1, 2020
PURPOSE: Pneumonia is a common clinical diagnosis for which chest radiographs are often an important part of the diagnostic workup. Deep learning has the potential to expedite and improve the clinical interpretation of chest radiographs. While earlie...
Child, Preschool Child Pneumonia Radiographic Image Interpretation, Computer-Assisted Probability Middle Aged Infant Lung Deep Learning Adolescent Radiography, Thoracic Humans Retrospective Studies Female Aged Aged, 80 and over Young Adult Adult Male
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Predicting Long-Term Outcomes After Poor-Grade Aneurysmal Subarachnoid Hemorrhage Using Decision Tree Modeling.

Neurosurgery Sep 1, 2020
BACKGROUND: Despite advances in the treatment of poor-grade aneurysmal subarachnoid hemorrhage (aSAH), predicting the long-term outcome of aSAH remains challenging, although essential.
Female Aged Adult Male Middle Aged ROC Curve Humans Machine Learning Prognosis Clinical Decision-Making Logistic Models Treatment Outcome Decision Trees Subarachnoid Hemorrhage
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Predicting Individual Remission After Electroconvulsive Therapy Based on Structural Magnetic Resonance Imaging: A Machine Learning Approach.

The journal of ECT Sep 1, 2020
OBJECTIVE: To identify important clinical or imaging features predictive of an individual's response to electroconvulsive therapy (ECT) by utilizing a machine learning approach.
Middle Aged Machine Learning Depressive Disorder, Major Brain Magnetic Resonance Imaging Electroconvulsive Therapy Female Predictive Value of Tests Aged Remission Induction Male Humans
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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 ...
Humans Administration, Oral Blood Coagulation Risk Assessment Atrial Fibrillation Reproducibility of Results International Normalized Ratio Neural Networks, Computer Time Factors Drug Monitoring Vitamin K Risk Factors Treatment Outcome Databases, Factual Registries Hemorrhage Aged Predictive Value of Tests Prospective Studies Stroke Prothrombin Time Aged, 80 and over Anticoagulants Female Drug Therapy, Computer-Assisted Male
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