AIMC Topic: False Positive Reactions

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Automatic CT image segmentation of maxillary sinus based on VGG network and improved V-Net.

International journal of computer assisted radiology and surgery Jul 16, 2020
PURPOSE: The analysis of the maxillary sinus (MS) can provide an assessment for many clinical diagnoses, so accurate CT image segmentation of the MS is essential. However, common segmentation methods are mainly done by experienced doctors manually, a...
Pattern Recognition, Automated False Positive Reactions Maxillary Sinus Reproducibility of Results Diagnosis, Computer-Assisted Imaging, Three-Dimensional Image Processing, Computer-Assisted Models, Statistical Humans Neural Networks, Computer Software Algorithms Tomography, X-Ray Computed
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Interactive machine learning for soybean seed and seedling quality classification.

Scientific reports Jul 9, 2020
New computer vision solutions combined with artificial intelligence algorithms can help recognize patterns in biological images, reducing subjectivity and optimizing the analysis process. The aim of this study was to propose an approach based on inte...
Artificial Intelligence Principal Component Analysis Software Germination Machine Learning Algorithms Seedlings Reproducibility of Results False Positive Reactions Image Processing, Computer-Assisted Glycine max Seeds
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CoroNet: A deep neural network for detection and diagnosis of COVID-19 from chest x-ray images.

Computer methods and programs in biomedicine Jun 5, 2020
BACKGROUND AND OBJECTIVE: The novel Coronavirus also called COVID-19 originated in Wuhan, China in December 2019 and has now spread across the world. It has so far infected around 1.8 million people and claimed approximately 114,698 lives overall. As...
Humans Neural Networks, Computer Coronavirus Infections Software False Positive Reactions Databases, Factual Pandemics Reproducibility of Results Radiography, Thoracic COVID-19 SARS-CoV-2 Betacoronavirus Algorithms Deep Learning Pneumonia, Viral Radiographic Image Interpretation, Computer-Assisted
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Diagnostic accuracy of diabetic retinopathy grading by an artificial intelligence-enabled algorithm compared with a human standard for wide-field true-colour confocal scanning and standard digital retinal images.

The British journal of ophthalmology May 6, 2020
BACKGROUND: Photographic diabetic retinopathy screening requires labour-intensive grading of retinal images by humans. Automated retinal image analysis software (ARIAS) could provide an alternative to human grading. We compare the performance of an A...
Microscopy, Confocal Predictive Value of Tests Diagnostic Imaging Retina Diagnostic Tests, Routine False Positive Reactions Reference Standards Slit Lamp Microscopy Humans Sensitivity and Specificity Diabetic Retinopathy Cross-Sectional Studies Female Artificial Intelligence Male Reproducibility of Results Algorithms Middle Aged Aged Image Processing, Computer-Assisted Adult
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Radiomics and deep learning in lung cancer.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] May 4, 2020
Lung malignancies have been extensively characterized through radiomics and deep learning. By providing a three-dimensional characterization of the lesion, models based on radiomic features from computed tomography (CT) and positron-emission tomograp...
Image Processing, Computer-Assisted Lung Neoplasms Genotype Computational Biology Treatment Outcome Phenotype Databases, Factual Prognosis Tomography, X-Ray Computed Deep Learning Radiotherapy Radiation Injuries Imaging Genomics Neoplasm Staging Neoplasm Recurrence, Local Radiotherapy Planning, Computer-Assisted False Positive Reactions Radiosurgery Humans Forecasting
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Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology Apr 27, 2020
Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR), chest computed tomography (CT) imaging may be a significantly more tr...
Humans Neural Networks, Computer Image Interpretation, Computer-Assisted False Negative Reactions False Positive Reactions Lung Pandemics Pneumonia, Viral Clinical Laboratory Techniques COVID-19 Deep Learning Betacoronavirus Tomography, X-Ray Computed Reverse Transcriptase Polymerase Chain Reaction SARS-CoV-2 Coronavirus Infections Sensitivity and Specificity COVID-19 Testing
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Machine Learning Algorithms in Suicide Prevention: Clinician Interpretations as Barriers to Implementation.

The Journal of clinical psychiatry Apr 21, 2020
OBJECTIVE: Machine learning algorithms in electronic medical records can classify patients by suicide risk, but no research has explored clinicians' perceptions of suicide risk flags generated by these algorithms, which may affect algorithm implement...
Female Adult Male Risk Assessment Attitude of Health Personnel Suicide Prevention False Negative Reactions False Positive Reactions Machine Learning Algorithms Health Personnel Physicians Electronic Health Records Humans
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Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans.

Medical physics Mar 18, 2020
PURPOSE: Multiview two-dimensional (2D) convolutional neural networks (CNNs) and three-dimensional (3D) CNNs have been successfully used for analyzing volumetric data in many state-of-the-art medical imaging applications. We propose an alternative mo...
Lung Neoplasms False Positive Reactions Radiography, Thoracic Humans Neural Networks, Computer Tomography, X-Ray Computed Sensitivity and Specificity Image Processing, Computer-Assisted
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A Machine-learning Approach to Forecast Aggravation Risk in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease with Clinical Indicators.

Scientific reports Feb 20, 2020
Patients with chronic obstructive pulmonary disease (COPD) repeat acute exacerbations (AE). Global Initiative for Chronic Obstructive Lung Disease (GOLD) is only available for patients in stable phase. Currently, there is a lack of assessment and pre...
Middle Aged Disease Progression Comorbidity ROC Curve Decision Support Systems, Clinical Humans Algorithms Aged Machine Learning Prognosis Aged, 80 and over Inflammation Female Adult Models, Statistical Reproducibility of Results Pulmonary Disease, Chronic Obstructive Decision Trees Hospitalization Male False Positive Reactions Risk
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Changes in cancer detection and false-positive recall in mammography using artificial intelligence: a retrospective, multireader study.

The Lancet. Digital health Feb 6, 2020
BACKGROUND: Mammography is the current standard for breast cancer screening. This study aimed to develop an artificial intelligence (AI) algorithm for diagnosis of breast cancer in mammography, and explore whether it could benefit radiologists by imp...
Radiology Observer Variation False Positive Reactions Humans Adult Artificial Intelligence Retrospective Studies Breast Neoplasms Female Middle Aged Early Detection of Cancer Mammography
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