AIMC Topic: False Positive Reactions

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Diagnostic performance of deep learning to exclude coronary stenosis on CT angiography in TAVI patients.

The international journal of cardiovascular imaging Mar 10, 2024
We evaluated the diagnostic performance of a deep-learning model (DLM) (CorEx®, Spimed-AI, Paris, France) designed to automatically detect > 50% coronary stenosis on coronary computed tomography angiography (CCTA) images. We studied inter-observer va...
Male Severity of Illness Index Deep Learning Aortic Valve Stenosis Aortic Valve Female Reproducibility of Results Aged Aged, 80 and over False Positive Reactions Multidetector Computed Tomography Computed Tomography Angiography Humans Coronary Stenosis Predictive Value of Tests Retrospective Studies Transcatheter Aortic Valve Replacement Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Observer Variation Coronary Vessels
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Reducing false positives in deep learning-based brain metastasis detection by using both gradient-echo and spin-echo contrast-enhanced MRI: validation in a multi-center diagnostic cohort.

European radiology Oct 28, 2023
OBJECTIVES: To develop a deep learning (DL) for detection of brain metastasis (BM) that incorporates both gradient- and turbo spin-echo contrast-enhanced MRI (dual-enhanced DL) and evaluate it in a clinical cohort in comparison with human readers and...
Male Middle Aged Deep Learning Cohort Studies Contrast Media Humans Magnetic Resonance Imaging Female False Positive Reactions Aged Aged, 80 and over Adult Sensitivity and Specificity Brain Neoplasms
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Machine learning to improve false-positive results in the Dutch newborn screening for congenital hypothyroidism.

Clinical biochemistry Mar 4, 2023
OBJECTIVE: The Dutch Congenital hypothyroidism (CH) Newborn Screening (NBS) algorithm for thyroidal and central congenital hypothyroidism (CH-T and CH-C, respectively) is primarily based on determination of thyroxine (T4) concentrations in dried bloo...
Thyroxine Neonatal Screening False Positive Reactions Gestational Age Congenital Hypothyroidism Humans Machine Learning Algorithms Infant, Newborn Random Forest Glycoprotein Hormones, alpha Subunit Thyroxine-Binding Globulin
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Breast Tumor Detection and Classification in Mammogram Images Using Modified YOLOv5 Network.

Computational and mathematical methods in medicine Jan 4, 2022
Breast cancer incidence has been rising steadily during the past few decades. It is the second leading cause of death in women. If it is diagnosed early, there is a good possibility of recovery. Mammography is proven to be an excellent screening tech...
Mammography Breast False Negative Reactions False Positive Reactions Radiographic Image Enhancement Sensitivity and Specificity Breast Neoplasms Diagnosis, Computer-Assisted Computational Biology Humans Neural Networks, Computer Machine Learning Databases, Factual Female
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Cataract Disease Detection by Using Transfer Learning-Based Intelligent Methods.

Computational and mathematical methods in medicine Dec 8, 2021
One of the most common visual disorders is cataracts, which people suffer from as they get older. The creation of a cloud on the lens of our eyes is known as a cataract. Blurred vision, faded colors, and difficulty seeing in strong light are the main...
False Positive Reactions Databases, Factual Humans Photography Computational Biology Neural Networks, Computer Cataract Machine Learning Image Interpretation, Computer-Assisted Algorithms False Negative Reactions
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Machine learning approach for the prediction of postpartum hemorrhage in vaginal birth.

Scientific reports Nov 19, 2021
Postpartum hemorrhage is the leading cause of maternal morbidity. Clinical prediction of postpartum hemorrhage remains challenging, particularly in the case of a vaginal birth. We studied machine learning models to predict postpartum hemorrhage. Wome...
Postpartum Hemorrhage Delivery, Obstetric Labor, Obstetric Tokyo Support Vector Machine Models, Statistical Area Under Curve Neural Networks, Computer False Positive Reactions Machine Learning Risk Pregnancy Reproducibility of Results Adolescent Humans Female Young Adult ROC Curve Infant, Newborn Adult Logistic Models Middle Aged Models, Theoretical Deep Learning
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Deep Learning Algorithm for COVID-19 Classification Using Chest X-Ray Images.

Computational and mathematical methods in medicine Nov 9, 2021
Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with clinical expertise, allows governments to break the transition chain and flatten the epidemic curve. Although reverse transcription-polymerase cha...
Early Diagnosis False Positive Reactions Radiography, Thoracic Software Design SARS-CoV-2 Humans Deep Learning Neural Networks, Computer ROC Curve Pandemics COVID-19 Testing COVID-19 Algorithms Databases, Factual Tomography, X-Ray Computed
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Revisiting performance metrics for prediction with rare outcomes.

Statistical methods in medical research Sep 1, 2021
Machine learning algorithms are increasingly used in the clinical literature, claiming advantages over logistic regression. However, they are generally designed to maximize the area under the receiver operating characteristic curve. While area under ...
ROC Curve Humans Predictive Value of Tests Machine Learning Benchmarking Algorithms False Positive Reactions Postoperative Complications
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Differentiation of Active Corneal Infections from Healed Scars Using Deep Learning.

Ophthalmology Aug 2, 2021
PURPOSE: To develop and evaluate an automated, portable algorithm to differentiate active corneal ulcers from healed scars using only external photographs.
Predictive Value of Tests Area Under Curve Cicatrix False Positive Reactions Eye Infections, Bacterial Photography Slit Lamp Microscopy Corneal Ulcer Eye Infections, Fungal Retrospective Studies Humans Sensitivity and Specificity Algorithms Deep Learning ROC Curve Wound Healing
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A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images.

JAMA network open Aug 2, 2021
IMPORTANCE: Breast cancer screening is among the most common radiological tasks, with more than 39 million examinations performed each year. While it has been among the most studied medical imaging applications of artificial intelligence, the develop...
Datasets as Topic Humans False Positive Reactions Deep Learning Female ROC Curve Reproducibility of Results Early Detection of Cancer Aged Mammography Breast Neoplasms Breast Middle Aged
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