AIMC Topic: Observer Variation
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Improving Ki67 assessment concordance by the use of an artificial intelligence-empowered microscope: a multi-institutional ring study.
Histopathology
Jun 24, 2021
AIMS: The nuclear proliferation biomarker Ki67 plays potential prognostic and predictive roles in breast cancer treatment. However, the lack of interpathologist consistency in Ki67 assessment limits the clinical use of Ki67. The aim of this article w...
Automating Periodontal bone loss measurement via dental landmark localisation.
International journal of computer assisted radiology and surgery
Jun 21, 2021
PURPOSE: Periodontitis is the sixth most prevalent disease worldwide and periodontal bone loss (PBL) detection is crucial for its early recognition and establishment of the correct diagnosis and prognosis. Current radiographic assessment by clinician...
Deep learning for classification of pediatric chest radiographs by WHO's standardized methodology.
PloS one
Jun 21, 2021
BACKGROUND: The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiveness studies in children. Automating the WHO methodology may support more widespread application of t...
Cardiothoracic ratio measurement using artificial intelligence: observer and method validation studies.
BMC medical imaging
Jun 7, 2021
BACKGROUND: Artificial Intelligence (AI) is a promising tool for cardiothoracic ratio (CTR) measurement that has been technically validated but not clinically evaluated on a large dataset. We observed and validated AI and manual methods for CTR measu...
The human-in-the-loop: an evaluation of pathologists' interaction with artificial intelligence in clinical practice.
Histopathology
May 30, 2021
AIMS: One of the major drivers of the adoption of digital pathology in clinical practice is the possibility of introducing digital image analysis (DIA) to assist with diagnostic tasks. This offers potential increases in accuracy, reproducibility, and...
Retrospective Studies
Reproducibility of Results
Breast Neoplasms
Biomarkers, Tumor
Humans
Artificial Intelligence
Research Design
Observer Variation
Immunohistochemistry
Calibration
Ki-67 Antigen
Pathology, Clinical
Diagnosis, Computer-Assisted
Image Processing, Computer-Assisted
Pathologists
Data Accuracy
Hopes and Hypes for Artificial Intelligence in Colorectal Cancer Screening.
Gastroenterology
May 11, 2021
Assistance from Automated ASPECTS Software Improves Reader Performance.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
May 11, 2021
PURPOSE: To compare physicians' ability to read Alberta Stroke Program Early CT Score (ASPECTS) in patients with a large vessel occlusion within 6 hours of symptom onset when assisted by a machine learning-based automatic software tool, compared with...
Automation
Middle Cerebral Artery
Carotid Artery, Internal
Neurologists
Male
Radiologists
Tomography, X-Ray Computed
Middle Aged
Humans
Radiographic Image Interpretation, Computer-Assisted
Female
Predictive Value of Tests
Clinical Competence
Machine Learning
Observer Variation
Reproducibility of Results
Magnetic Resonance Imaging
Software
Ischemic Stroke
Aged
Prognosis
Development of a Method for Clinical Evaluation of Artificial Intelligence-Based Digital Wound Assessment Tools.
JAMA network open
May 3, 2021
IMPORTANCE: Accurate assessment of wound area and percentage of granulation tissue (PGT) are important for optimizing wound care and healing outcomes. Artificial intelligence (AI)-based wound assessment tools have the potential to improve the accurac...
Prospective assessment of breast cancer risk from multimodal multiview ultrasound images via clinically applicable deep learning.
Nature biomedical engineering
Apr 19, 2021
The clinical application of breast ultrasound for the assessment of cancer risk and of deep learning for the classification of breast-ultrasound images has been hindered by inter-grader variability and high false positive rates and by deep-learning m...
Multibeat echocardiographic phase detection using deep neural networks.
Computers in biology and medicine
Apr 6, 2021
BACKGROUND: Accurate identification of end-diastolic and end-systolic frames in echocardiographic cine loops is important, yet challenging, for human experts. Manual frame selection is subject to uncertainty, affecting crucial clinical measurements, ...
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