AIMC Topic: Observer Variation

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Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.

The international journal of cardiovascular imaging Apr 17, 2024
This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who und...
Aged Male Middle Aged Severity of Illness Index Predictive Value of Tests Humans Artificial Intelligence Female Reproducibility of Results Coronary Stenosis Coronary Vessels Multidetector Computed Tomography Plaque, Atherosclerotic Vascular Calcification Computed Tomography Angiography Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Observer Variation
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An artificial intelligence-driven scoring system to measure histological disease activity in ulcerative colitis.

United European gastroenterology journal Apr 8, 2024
BACKGROUND AND AIMS: Assessment and scoring of histological images in Ulcerative colitis (UC) is prone to inter- and intra-observer variability. This study aimed to investigate whether an artificial intelligence (AI) system developed using image proc...
Image Interpretation, Computer-Assisted Observer Variation Severity of Illness Index Humans Algorithms Deep Learning Artificial Intelligence Female Image Processing, Computer-Assisted Machine Learning Reproducibility of Results Colitis, Ulcerative Male Colon
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Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments.

Virchows Archiv : an international journal of pathology Apr 4, 2024
Assessing programmed death ligand 1 (PD-L1) expression on tumor cells (TCs) using Food and Drug Administration-approved, validated immunoassays can guide the use of immune checkpoint inhibitor (ICI) therapy in cancer treatment. However, substantial i...
Humans Artificial Intelligence Reproducibility of Results Pathologists Observer Variation Immunohistochemistry Carcinoma, Transitional Cell Urothelium Biomarkers, Tumor B7-H1 Antigen Urologic Neoplasms Urinary Bladder Neoplasms
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Echocardiographic Detection of Regional Wall Motion Abnormalities Using Artificial Intelligence Compared to Human Readers.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Mar 30, 2024
BACKGROUND: Although regional wall motion abnormality (RWMA) detection is foundational to transthoracic echocardiography, current methods are prone to interobserver variability. We aimed to develop a deep learning (DL) model for RWMA assessment and c...
Deep Learning Aged Humans Male Ventricular Dysfunction, Left Artificial Intelligence Echocardiography Image Interpretation, Computer-Assisted Female Middle Aged Observer Variation Reproducibility of Results
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Deep Learning-Derived Myocardial Strain.

JACC. Cardiovascular imaging Mar 27, 2024
BACKGROUND: Echocardiographic strain measurements require extensive operator experience and have significant intervendor variability. Creating an automated, open-source, vendor-agnostic method to retrospectively measure global longitudinal strain (GL...
Middle Aged Deep Learning Predictive Value of Tests Image Interpretation, Computer-Assisted Observer Variation Automation Humans Biomechanical Phenomena Myocardial Contraction Retrospective Studies Male Female Ventricular Function, Left Reproducibility of Results Echocardiography Aged
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Quality assurance of late gadolinium enhancement cardiac magnetic resonance images: a deep learning classifier for confidence in the presence or absence of abnormality with potential to prompt real-time image optimization.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Mar 24, 2024
BACKGROUND: Late gadolinium enhancement (LGE) of the myocardium has significant diagnostic and prognostic implications, with even small areas of enhancement being important. Distinguishing between definitely normal and definitely abnormal LGE images ...
Magnetic Resonance Imaging, Cine Female Myocardium Reproducibility of Results Heart Diseases Humans Aged Image Interpretation, Computer-Assisted Databases, Factual Male Deep Learning Quality Assurance, Health Care Middle Aged Observer Variation Contrast Media Magnetic Resonance Imaging Predictive Value of Tests
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Inter-reviewer reliability of human literature reviewing and implications for the introduction of machine-assisted systematic reviews: a mixed-methods review.

BMJ open Mar 19, 2024
OBJECTIVES: Our main objective is to assess the inter-reviewer reliability (IRR) reported in published systematic literature reviews (SLRs). Our secondary objective is to determine the expected IRR by authors of SLRs for both human and machine-assist...
Humans Machine Learning Reproducibility of Results Systematic Reviews as Topic Observer Variation
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An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

Histopathology Mar 13, 2024
AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between path...
Humans Artificial Intelligence Female Aged Urologic Neoplasms Biomarkers, Tumor Urinary Bladder Neoplasms Male Observer Variation B7-H1 Antigen Immunohistochemistry Carcinoma, Transitional Cell
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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...
False Positive Reactions Multidetector Computed Tomography Computed Tomography Angiography Coronary Stenosis Transcatheter Aortic Valve Replacement Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Observer Variation Coronary Vessels Reproducibility of Results Aged Aged, 80 and over Male Severity of Illness Index Deep Learning Aortic Valve Stenosis Aortic Valve Predictive Value of Tests Humans Retrospective Studies Female
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A fully automated artificial intelligence-driven software for planning of transcatheter aortic valve replacement.

Cardiovascular revascularization medicine : including molecular interventions Mar 7, 2024
BACKGROUND: Transcatheter aortic valve replacement (TAVR) is increasingly performed for the treatment of aortic stenosis. Computed tomography (CT) analysis is essential for pre-procedural planning. Currently available software packages for TAVR plann...
Humans Transcatheter Aortic Valve Replacement Observer Variation Artificial Intelligence Software Validation Software Automation Reproducibility of Results Multidetector Computed Tomography Aortic Valve Stenosis Heart Valve Prosthesis Aortic Valve Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Prosthesis Design
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