AIMC Topic: Retrospective Studies

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A combined ultrasonic B-mode and color Doppler system for the classification of breast masses using neural network.

European radiology Jan 31, 2020
OBJECTIVES: To develop a dual-modal neural network model to characterize ultrasound (US) images of breast masses.
Radiologists Humans Ultrasonography, Mammary Neural Networks, Computer Ultrasonography, Doppler, Color Retrospective Studies Sensitivity and Specificity Female Aged Breast Neoplasms Adult Middle Aged ROC Curve Area Under Curve
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The influence of image quality on diagnostic performance of a machine learning-based fractional flow reserve derived from coronary CT angiography.

European radiology Jan 31, 2020
OBJECTIVE: To investigate the effect of image quality of coronary CT angiography (CCTA) on the diagnostic performance of a machine learning-based CT-derived fractional flow reserve (FFR).
Male Middle Aged Coronary Angiography Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Machine Learning Retrospective Studies Female Reproducibility of Results Aged Humans
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Prediction of vaginal birth after cesarean deliveries using machine learning.

American journal of obstetrics and gynecology Jan 30, 2020
BACKGROUND: Efforts to reduce cesarean delivery rates to 12-15% have been undertaken worldwide. Special focus has been directed towards parturients who undergo a trial of labor after cesarean delivery to reduce the burden of repeated cesarean deliver...
Trial of Labor Uterine Rupture Vaginal Birth after Cesarean Delivery, Obstetric Adult Apgar Score Humans Female Area Under Curve Risk Assessment Fetal Weight Machine Learning Infant, Newborn Tertiary Care Centers ROC Curve Extraction, Obstetrical Retrospective Studies Cesarean Section Feasibility Studies Organ Size Pregnancy Parity Head Risk Factors Gestational Age
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Machine Learning for Predicting Complications in Head and Neck Microvascular Free Tissue Transfer.

The Laryngoscope Jan 28, 2020
OBJECTIVES/HYPOTHESIS: Machine learning (ML) is a type of artificial intelligence wherein a computer learns patterns and associations between variables to correctly predict outcomes. The objectives of this study were to 1) use a ML platform to identi...
Aged, 80 and over Male Middle Aged Postoperative Complications Cohort Studies Head and Neck Neoplasms Plastic Surgery Procedures Free Tissue Flaps Microvessels Machine Learning Prognosis Retrospective Studies Female Aged Humans
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A machine learning approach for differentiating malignant from benign enhancing foci on breast MRI.

European radiology experimental Jan 28, 2020
BACKGROUND: Differentiate malignant from benign enhancing foci on breast magnetic resonance imaging (MRI) through radiomic signature.
Humans Machine Learning Organometallic Compounds Retrospective Studies Contrast Media Female Meglumine Magnetic Resonance Imaging Adult Diagnosis, Differential Breast Neoplasms Feasibility Studies Middle Aged Image Interpretation, Computer-Assisted
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Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method.

European radiology experimental Jan 28, 2020
BACKGROUND: Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time efficiency in daily routine. The aim of this study was to investigate the accuracy and efficiency of a ...
Hand Germany Age Determination by Skeleton Humans Artificial Intelligence Retrospective Studies Adolescent Child, Preschool Child Radiography Wrist
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Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie Jan 27, 2020
PURPOSE: To develop a deep learning approach based on deep residual neural network (ResNet101) for the automated detection of glaucomatous optic neuropathy (GON) using color fundus images, understand the process by which the model makes predictions, ...
Intraocular Pressure Deep Learning ROC Curve Tomography, Optical Coherence Optic Disk Humans Neural Networks, Computer Glaucoma Retrospective Studies Retinal Ganglion Cells Optic Nerve Diseases Diagnostic Techniques, Ophthalmological
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Convolutional neural network enhancement of fast-scan low-dose cone-beam CT images for head and neck radiotherapy.

Physics in medicine and biology Jan 27, 2020
To improve image quality and CT number accuracy of fast-scan low-dose cone-beam computed tomography (CBCT) through a deep-learning convolutional neural network (CNN) methodology for head-and-neck (HN) radiotherapy. Fifty-five paired CBCT and CT image...
Head and Neck Neoplasms Radiotherapy Planning, Computer-Assisted Humans Image Enhancement Neural Networks, Computer Signal-To-Noise Ratio Retrospective Studies Cone-Beam Computed Tomography Image Processing, Computer-Assisted
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Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society Jan 24, 2020
OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...
Artificial Intelligence Retrospective Studies Female Reproducibility of Results Aged Humans Neural Networks, Computer Outcome Assessment, Health Care Esophageal Squamous Cell Carcinoma Preoperative Care Endoscopic Mucosal Resection Deep Learning Neoplasm Invasiveness Area Under Curve Esophageal Neoplasms Japan Aged, 80 and over Sensitivity and Specificity Male Middle Aged
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Observer-independent assessment of psoriasis-affected area using machine learning.

Journal of the European Academy of Dermatology and Venereology : JEADV Jan 23, 2020
BACKGROUND: Assessment of psoriasis severity is strongly observer-dependent, and objective assessment tools are largely missing. The increasing number of patients receiving highly expensive therapies that are reimbursed only for moderate-to-severe ps...
Humans Neural Networks, Computer Machine Learning Retrospective Studies Reproducibility of Results Severity of Illness Index Adolescent Aged Psoriasis Aged, 80 and over Observer Variation Photography Young Adult Adult Middle Aged
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