AIMC Topic:
Predictive Value of Tests

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Machine Learning-Based Prediction of Clinical Outcomes for Children During Emergency Department Triage.

JAMA network open Jan 4, 2019
IMPORTANCE: While machine learning approaches may enhance prediction ability, little is known about their utility in emergency department (ED) triage.
Machine Learning Prognosis Female Hospitalization Male Humans Predictive Value of Tests Triage Emergency Service, Hospital Critical Care Quality Improvement Adolescent Child, Preschool Child United States Critical Care Outcomes Models, Educational Child, Hospitalized
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Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

La Radiologia medica Jan 3, 2019
OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiomic features and machine learning methods to predict early intensity-modulated radiation therapy (IMRT) response, Gleason scores (GS) and prostate canc...
Middle Aged Treatment Outcome Magnetic Resonance Imaging Predictive Value of Tests Machine Learning Prostatic Neoplasms Humans Prospective Studies Neoplasm Staging Aged Neoplasm Grading Aged, 80 and over Image Interpretation, Computer-Assisted Male Radiotherapy, Intensity-Modulated
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Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status.

AJR. American journal of roentgenology Jan 2, 2019
OBJECTIVE: The purpose of this study is to evaluate the potential value of machine learning (ML)-based high-dimensional quantitative CT texture analysis in predicting the mutation status of the gene encoding the protein polybromo-1 (PBRM1) in patient...
Tomography, X-Ray Computed Female Reproducibility of Results Aged Male Humans Machine Learning Algorithms Retrospective Studies Mutation Radiographic Image Interpretation, Computer-Assisted DNA-Binding Proteins Kidney Neoplasms Carcinoma, Renal Cell Middle Aged Nuclear Proteins Transcription Factors Contrast Media Predictive Value of Tests
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A novel prediction method for lymph node involvement in endometrial cancer: machine learning.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society Dec 28, 2018
OBJECTIVE: The necessity of lymphadenectomy and the prediction of lymph node involvement (LNI) in endometrial cancer (EC) have been hotly-debated questions in recent years. Machine learning is a broad field that can produce results and estimations. I...
Adult Middle Aged Lymph Nodes Humans Follow-Up Studies Machine Learning Lymph Node Excision Models, Statistical Retrospective Studies Predictive Value of Tests Female Endometrial Neoplasms Aged Aged, 80 and over
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Automated data extraction and ensemble methods for predictive modeling of breast cancer outcomes after radiation therapy.

Medical physics Dec 28, 2018
PURPOSE: The purpose of this study was to compare the effectiveness of ensemble methods (e.g., random forests) and single-model methods (e.g., logistic regression and decision trees) in predictive modeling of post-RT treatment failure and adverse eve...
Predictive Value of Tests Data Mining Radiotherapy Dosage Humans Machine Learning Electronic Health Records Female Breast Neoplasms Middle Aged Treatment Outcome Decision Trees
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Predicting persistent depressive symptoms in older adults: A machine learning approach to personalised mental healthcare.

Journal of affective disorders Dec 25, 2018
BACKGROUND: Depression causes significant physical and psychosocial morbidity. Predicting persistence of depressive symptoms could permit targeted prevention, and lessen the burden of depression. Machine learning is a rapidly expanding field, and suc...
Risk Assessment Delivery of Health Care Psychiatric Status Rating Scales Follow-Up Studies Female Humans Depression Aged Age Factors Machine Learning Logistic Models Aged, 80 and over Predictive Value of Tests Algorithms Male Decision Support Techniques
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Prediction and evaluation of the severity of acute respiratory distress syndrome following severe acute pancreatitis using an artificial neural network algorithm model.

HPB : the official journal of the International Hepato Pancreato Biliary Association Dec 24, 2018
BACKGROUND: To predict the risk and severity of acute respiratory distress syndrome (ARDS) following severe acute pancreatitis (SAP) by artificial neural networks (ANNs) model.
Risk Assessment Severity of Illness Index Neural Networks, Computer Respiratory Distress Syndrome Decision Support Techniques Predictive Value of Tests Prognosis Risk Factors Pancreatitis Female Adult Reproducibility of Results Humans Male Middle Aged
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PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data.

BMC bioinformatics Dec 17, 2018
BACKGROUND: Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis may be caused by high complexity of ...
Humans Neural Networks, Computer Software Prognosis Biomarkers, Tumor Predictive Value of Tests Glioblastoma Area Under Curve High-Throughput Nucleotide Sequencing
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Predicting instructed simulation and dissimulation when screening for depressive symptoms.

European archives of psychiatry and clinical neuroscience Dec 12, 2018
The intentional distortion of test results presents a fundamental problem to self-report-based psychiatric assessment, such as screening for depressive symptoms. The first objective of the study was to clarify whether depressed patients like healthy ...
Supervised Machine Learning Malingering Male Humans Depression Female Psychometrics Young Adult Deception Adult Predictive Value of Tests
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Prediction of Lymph Node Maximum Standardized Uptake Value in Patients With Cancer Using a 3D Convolutional Neural Network: A Proof-of-Concept Study.

AJR. American journal of roentgenology Dec 12, 2018
OBJECTIVE: The purpose of this study is to determine whether a convolutional neural network (CNN) can predict the maximum standardized uptake value (SUV) of lymph nodes in patients with cancer using the unenhanced CT images from a PET/CT examination,...
Proof of Concept Study Lymphatic Metastasis Predictive Value of Tests Positron Emission Tomography Computed Tomography Radiopharmaceuticals Fluorodeoxyglucose F18 Adult Middle Aged Neoplasms Imaging, Three-Dimensional Humans Neural Networks, Computer Retrospective Studies Tomography, X-Ray Computed Aged Aged, 80 and over Young Adult
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