AIMC Topic: Predictive Value of Tests

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Application of an artificial neural network model for early outcome prediction of gamma knife radiosurgery in patients with trigeminal neuralgia and determining the relative importance of risk factors.

Clinical neurology and neurosurgery Feb 12, 2019
OBJECTIVES: Stereotactic radiosurgery (SRS) is a minimally invasive modality for the treatment of trigeminal neuralgia (TN). Outcome prediction of this modality is very important for proper case selection. The aim of this study was to create artifici...
Radiosurgery Trigeminal Neuralgia Kaplan-Meier Estimate Follow-Up Studies Predictive Value of Tests Pain Measurement Neurosurgical Procedures Radiation Dosage Depression Adolescent Humans Treatment Outcome Diabetes Mellitus Aged, 80 and over Neural Networks, Computer Young Adult Prognosis Adult Female Male Risk Factors Middle Aged Aged
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A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models.

Journal of clinical epidemiology Feb 11, 2019
OBJECTIVES: The objective of this study was to compare performance of logistic regression (LR) with machine learning (ML) for clinical prediction modeling in the literature.
Area Under Curve Supervised Machine Learning Outcome Assessment, Health Care Algorithms Sensitivity and Specificity Logistic Models Models, Theoretical Predictive Value of Tests Humans
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An integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation Feb 6, 2019
BACKGROUND: We previously reported a microarray-based diagnostic system for heart transplant endomyocardial biopsies (EMBs), using either 3-archetype (3AA) or 4-archetype (4AA) unsupervised algorithms to estimate rejection. In the present study we ex...
Humans Machine Learning Algorithms Female Aged Young Adult Adult Myocardium Heart Failure Heart Transplantation Pathology, Molecular Child, Preschool Child ROC Curve Predictive Value of Tests Graft Rejection Male Middle Aged Risk Assessment Adolescent Cohort Studies
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The use of artificial neural network analysis can improve the risk-stratification of patients presenting with suspected deep vein thrombosis.

British journal of haematology Feb 6, 2019
Artificial neural networks are machine-learning algorithms designed to analyse data without a pre-existing hypothesis as to any associations that may exist. This technique has not previously been applied to the risk stratification of patients referre...
Neural Networks, Computer Algorithms Biomarkers Retrospective Studies Female Humans Fibrin Fibrinogen Degradation Products Ultrasonography Adult Venous Thrombosis Male Predictive Value of Tests Middle Aged False Negative Reactions Risk Assessment Proof of Concept Study
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Severe Dengue Prognosis Using Human Genome Data and Machine Learning.

IEEE transactions on bio-medical engineering Feb 4, 2019
UNLABELLED: Dengue has become one of the most important worldwide arthropod-borne diseases. Dengue phenotypes are based on laboratorial and clinical exams, which are known to be inaccurate.
Humans Predictive Value of Tests Machine Learning Genome, Human Phenotype Sensitivity and Specificity Severe Dengue Prognosis Brazil Case-Control Studies Polymorphism, Single Nucleotide Genotype
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An Intelligent Clinical Decision Support System for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer.

Journal of the American College of Radiology : JACR Feb 4, 2019
PURPOSE: The aim of this study was to develop and validate a computational clinical decision support system (DSS) on the basis of CT radiomics features for the prediction of lymph node (LN) metastasis in gastric cancer (GC) using machine learning-bas...
Decision Support Systems, Clinical Lymph Nodes Lymphatic Metastasis Neoplasm Invasiveness Predictive Value of Tests Aged Stomach Neoplasms Male Middle Aged ROC Curve Neoplasm Staging Gastrectomy Multidetector Computed Tomography Preoperative Care Humans Machine Learning Databases, Factual Prognosis Retrospective Studies Clinical Decision-Making Female
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Potential roles of artificial intelligence learning and faecal immunochemical testing for prioritisation of colonoscopy in anaemia.

British journal of haematology Feb 3, 2019
Iron deficiency anaemia (IDA) is the most common cause of anaemia and a frequent indication for colonoscopy, although the prevalence of colorectal cancer (CRC) in IDA is low. Measurement of faecal haemoglobin by immunochemical techniques (FIT) is use...
Female Aged Aged, 80 and over Adult Sensitivity and Specificity Humans Artificial Intelligence Early Detection of Cancer Predictive Value of Tests Anemia, Iron-Deficiency Referral and Consultation Occult Blood Colorectal Neoplasms Male Middle Aged Colonoscopy Cohort Studies
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How Should AI Be Developed, Validated, and Implemented in Patient Care?

AMA journal of ethics Feb 1, 2019
Should an artificial intelligence (AI) program that appears to have a better success rate than human pathologists be used to replace or augment humans in detecting cancer cells? We argue that some concerns-the "black-box" problem (ie, the unknowabili...
Early Detection of Cancer Humans Predictive Value of Tests Artificial Intelligence Patient Care Female Adult Breast Neoplasms Diagnosis, Computer-Assisted
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Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data.

Medical image analysis Jan 30, 2019
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the earl...
Predictive Value of Tests Alzheimer Disease Humans Machine Learning Computer Simulation Female Aged Male Disease Progression Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Machine Learning to Predict Delays in Adjuvant Radiation following Surgery for Head and Neck Cancer.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Jan 29, 2019
OBJECTIVE: To apply a novel methodology with machine learning (ML) to a large national cancer registry to help identify patients who are high risk for delayed adjuvant radiation.
Predictive Value of Tests Neoplasm Staging Time-to-Treatment Radiotherapy, Adjuvant Middle Aged Cohort Studies United States Socioeconomic Factors Head and Neck Neoplasms Databases, Factual Female Humans Carcinoma, Squamous Cell Machine Learning Aged Algorithms Male
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