AIMC Topic: Diagnosis, Differential

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Automated classification of solid renal masses on contrast-enhanced computed tomography images using convolutional neural network with decision fusion.

European radiology Apr 29, 2020
OBJECTIVES: To develop a deep learning-based method for automated classification of renal cell carcinoma (RCC) from benign solid renal masses using contrast-enhanced computed tomography (CECT) images.
Diagnosis, Differential Image Interpretation, Computer-Assisted Kidney Neoplasms Carcinoma, Renal Cell Angiomyolipoma Adenoma, Oxyphilic Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Contrast Media Humans Neural Networks, Computer
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Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Biochimica et biophysica acta. Molecular basis of disease Apr 28, 2020
Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in sever...
Adenocarcinoma of Lung Cystatin A Gene Expression Profiling Adenosine Triphosphatases Humans Transcription Factors Transcriptome Terminology as Topic Machine Learning Diagnosis, Differential Lung Neoplasms Membrane Transport Proteins Carcinoma, Squamous Cell Cadherins Computational Biology Monte Carlo Method Datasets as Topic Gene Expression Regulation, Neoplastic Serpins Tumor Suppressor Proteins
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Artificial Intelligence-Based Differential Diagnosis: Development and Validation of a Probabilistic Model to Address Lack of Large-Scale Clinical Datasets.

Journal of medical Internet research Apr 28, 2020
BACKGROUND: Machine-learning or deep-learning algorithms for clinical diagnosis are inherently dependent on the availability of large-scale clinical datasets. Lack of such datasets and inherent problems such as overfitting often necessitate the devel...
Diagnosis, Differential Humans Artificial Intelligence Algorithms Models, Statistical
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Artificial Intelligence Augmentation of Radiologist Performance in Distinguishing COVID-19 from Pneumonia of Other Origin at Chest CT.

Radiology Apr 27, 2020
Background Coronavirus disease 2019 (COVID-19) and pneumonia of other diseases share similar CT characteristics, which contributes to the challenges in differentiating them with high accuracy. Purpose To establish and evaluate an artificial intellige...
Male Middle Aged Infant Lung China Aged, 80 and over Young Adult Adult Sensitivity and Specificity Radiologists Coronavirus Infections Radiography, Thoracic Philadelphia Rhode Island Adolescent Child, Preschool Child Diagnosis, Differential Pneumonia Humans Artificial Intelligence Pandemics COVID-19 Retrospective Studies Tomography, X-Ray Computed Female Infant, Newborn SARS-CoV-2 Aged Betacoronavirus Pneumonia, Viral
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Ependymoma and pilocytic astrocytoma: Differentiation using radiomics approach based on machine learning.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia Apr 23, 2020
Mandatory accurate and specific diagnosis demands have brought about increased challenges for radiologists in pediatric posterior fossa tumor prediction and prognosis. With the development of high-performance computing and machine learning technologi...
Child, Preschool Child Female Magnetic Resonance Imaging Infant, Newborn Diagnosis, Differential Male Image Interpretation, Computer-Assisted Infant Astrocytoma Humans Adolescent Ependymoma Machine Learning Infratentorial Neoplasms
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A novel and simple machine learning algorithm for preoperative diagnosis of acute appendicitis in children.

Pediatric surgery international Apr 20, 2020
INTRODUCTION: There is a tendency toward nonoperative management of appendicitis resulting in an increasing need for preoperative diagnosis and classification. For medical purposes, simple conceptual decision-making models that can learn are widely u...
Diagnosis, Differential Acute Disease Appendicitis Preoperative Period Female Appendectomy Male Child, Preschool Child Humans Machine Learning Algorithms
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Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography.

PloS one Apr 16, 2020
This study examined and compared outcomes of deep learning (DL) in identifying swept-source optical coherence tomography (OCT) images without myopic macular lesions [i.e., no high myopia (nHM) vs. high myopia (HM)], and OCT images with myopic macular...
Retinoschisis Male ROC Curve Image Interpretation, Computer-Assisted Humans Mass Screening Middle Aged Datasets as Topic Diagnosis, Differential Female Myopia Macula Lutea Choroid Aged Severity of Illness Index Blindness Tomography, Optical Coherence Adult Deep Learning Choroidal Neovascularization
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Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs.

The New England journal of medicine Apr 14, 2020
BACKGROUND: Nonophthalmologist physicians do not confidently perform direct ophthalmoscopy. The use of artificial intelligence to detect papilledema and other optic-disk abnormalities from fundus photographs has not been well studied.
Diagnosis, Differential Predictive Value of Tests Area Under Curve Fundus Oculi Retina Algorithms Retrospective Studies Sensitivity and Specificity Humans Deep Learning Datasets as Topic Neural Networks, Computer ROC Curve Ophthalmoscopy Photography Papilledema
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Differential Diagnosis of Benign and Malignant Thyroid Nodules Using Deep Learning Radiomics of Thyroid Ultrasound Images.

European journal of radiology Apr 12, 2020
PURPOSE: We aimed to propose a highly automatic and objective model named deep learning Radiomics of thyroid (DLRT) for the differential diagnosis of benign and malignant thyroid nodules from ultrasound (US) images.
Cohort Studies Ultrasonography Thyroid Nodule Reproducibility of Results Humans ROC Curve Area Under Curve Male Retrospective Studies Diagnosis, Differential Middle Aged Image Interpretation, Computer-Assisted Female Deep Learning Thyroid Gland
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Fellow in a Box: Combining AI and Domain Knowledge with Bayesian Networks for Differential Diagnosis in Neuroimaging.

Radiology Apr 7, 2020
Brain Magnetic Resonance Imaging Diagnosis, Differential Bayes Theorem Neuroimaging Artificial Intelligence
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