AIMC Topic:
Image Interpretation, Computer-Assisted

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Development and validation of a deep learning system for ascites cytopathology interpretation.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association Jun 4, 2020
BACKGROUND: Early diagnosis of Peritoneal metastasis (PM) is clinically significant regarding optimal treatment selection and avoidance of unnecessary surgical procedures. Cytopathology plays an important role in early screening of PM. We aimed to de...
Deep Learning Early Detection of Cancer Area Under Curve Ascites Peritoneal Neoplasms Humans Neural Networks, Computer Reproducibility of Results Image Interpretation, Computer-Assisted Neoplasm Metastasis Datasets as Topic
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Implementation of model explainability for a basic brain tumor detection using convolutional neural networks on MRI slices.

Neuroradiology Jun 4, 2020
PURPOSE: While neural networks gain popularity in medical research, attempts to make the decisions of a model explainable are often only made towards the end of the development process once a high predictive accuracy has been achieved.
Diagnosis, Differential Glioblastoma Bayes Theorem Image Interpretation, Computer-Assisted Datasets as Topic Neurilemmoma Neural Networks, Computer Brain Neoplasms Contrast Media Magnetic Resonance Imaging Humans
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An innovative method for screening and evaluating the degree of diabetic retinopathy and drug treatment based on artificial intelligence algorithms.

Pharmacological research Jun 2, 2020
Current methods of evaluating the degree of diabetic retinopathy are highly subjective and have no quantitative standard. To objectively evaluate the slight changes in tissue structure during the early stage of retinal diseases, a subjective interpre...
Image Interpretation, Computer-Assisted Early Diagnosis Retinal Ganglion Cells Pattern Recognition, Automated Drugs, Chinese Herbal Diabetes Mellitus, Experimental Retina Microscopy Retinal Vessels Male Severity of Illness Index Deep Learning Diabetes Mellitus, Type 2 Diabetes Mellitus, Type 1 Hypoglycemic Agents Predictive Value of Tests Mice Rats, Wistar Diabetic Retinopathy Animals
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Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma.

BMC cancer Jun 1, 2020
BACKGROUND: Early radiation-induced temporal lobe injury (RTLI) diagnosis in nasopharyngeal carcinoma (NPC) is clinically challenging, and prediction models of RTLI are lacking. Hence, we aimed to develop radiomic models for early detection of RTLI.
Middle Aged ROC Curve Longitudinal Studies Magnetic Resonance Imaging Retrospective Studies Female Adult Male Image Interpretation, Computer-Assisted Radiation Injuries Nasopharyngeal Carcinoma Nasopharyngeal Neoplasms Temporal Lobe Brain Injuries Predictive Value of Tests Aftercare Models, Biological Humans Machine Learning Algorithms
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AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction.

NeuroImage. Clinical Jun 1, 2020
The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective intervention and patient selection in clinical trials. Different biomarkers including neuroimaging have...
Image Interpretation, Computer-Assisted Cognitive Dysfunction Humans Age Factors Pattern Recognition, Automated Neural Networks, Computer Predictive Value of Tests Neuroimaging Brain Alzheimer Disease Disease Progression
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Deep learning shows the capability of high-level computer-aided diagnosis in malignant lymphoma.

Laboratory investigation; a journal of technical methods and pathology May 29, 2020
A pathological evaluation is one of the most important methods for the diagnosis of malignant lymphoma. A standardized diagnosis is occasionally difficult to achieve even by experienced hematopathologists. Therefore, established procedures including ...
Humans Neural Networks, Computer Algorithms Lymphoma, Follicular Pseudolymphoma Pathologists Image Interpretation, Computer-Assisted Observer Variation Histological Techniques Lymphoma, Large B-Cell, Diffuse Diagnosis, Computer-Assisted Deep Learning Lymphoma
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Using X-ray images and deep learning for automated detection of coronavirus disease.

Journal of biomolecular structure & dynamics May 22, 2020
Coronavirus is still the leading cause of death worldwide. There are a set number of COVID-19 test units accessible in emergency clinics because of the expanding cases daily. Therefore, it is important to implement an automatic detection and classifi...
Image Interpretation, Computer-Assisted X-Rays Humans COVID-19 Diagnosis, Computer-Assisted Deep Learning
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Fully Automated Segmentation of Globes for Volume Quantification in CT Images of Orbits using Deep Learning.

AJNR. American journal of neuroradiology May 21, 2020
BACKGROUND AND PURPOSE: Fast and accurate quantification of globe volumes in the event of an ocular trauma can provide clinicians with valuable diagnostic information. In this work, an automated workflow using a deep learning-based convolutional neur...
Humans Tomography, X-Ray Computed Image Interpretation, Computer-Assisted Observer Variation Neuroimaging Deep Learning Orbit
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Multi-instance Deep Learning of Ultrasound Imaging Data for Pattern Classification of Congenital Abnormalities of the Kidney and Urinary Tract in Children.

Urology May 20, 2020
OBJECTIVE: To reliably and quickly diagnose children with posterior urethral valves (PUV), we developed a multi-instance deep learning method to automate image analysis.
ROC Curve Kidney Humans Diagnosis, Differential Urogenital Abnormalities Female Feasibility Studies Infant, Newborn Infant Reproducibility of Results Image Interpretation, Computer-Assisted Case-Control Studies Male Vesico-Ureteral Reflux Deep Learning Hydronephrosis Ultrasonography Urethra
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An automated machine learning approach to predict brain age from cortical anatomical measures.

Human brain mapping May 16, 2020
The use of machine learning (ML) algorithms has significantly increased in neuroscience. However, from the vast extent of possible ML algorithms, which one is the optimal model to predict the target variable? What are the hyperparameters for such a m...
Age Factors Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Datasets as Topic Humans Neuroimaging Machine Learning Cerebral Cortex Female Middle Aged Aged Adolescent Aged, 80 and over Image Processing, Computer-Assisted Young Adult Models, Theoretical Adult Male
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