AI Medical Compendium Topic:
Diagnosis, Differential

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DrKnow: A Diagnostic Learning Tool with Feedback from Automated Clinical Decision Support.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Providing medical trainees with effective feedback is critical to the successful development of their diagnostic reasoning skills. We present the design of DrKnow, a web-based learning application that utilises a clinical decision support system (CDS...
Feedback Decision Support Systems, Clinical Diagnosis, Differential Abdominal Pain Humans Machine Learning Students, Medical Internet Education, Medical, Undergraduate Simulation Training Teaching Computer-Assisted Instruction
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Improving the calling of non-invasive prenatal testing on 13-/18-/21-trisomy by support vector machine discrimination.

PloS one Dec 5, 2018
With the advance of next-generation sequencing (NGS) technologies, non-invasive prenatal testing (NIPT) has been developed and employed in fetal aneuploidy screening on 13-/18-/21-trisomies through detecting cell-free fetal DNA (cffDNA) in maternal b...
High-Throughput Nucleotide Sequencing Down Syndrome False Negative Reactions False Positive Reactions Trisomy 18 Syndrome Humans Prenatal Diagnosis Machine Learning Trisomy 13 Syndrome Retrospective Studies Pregnancy Female Young Adult Adult Diagnosis, Computer-Assisted Support Vector Machine Sequence Analysis, DNA Diagnosis, Differential Genetic Testing
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Patch-based system for Classification of Breast Histology images using deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Dec 1, 2018
In this work, we proposed a patch-based classifier (PBC) using Convolutional neural network (CNN) for automatic classification of histopathological breast images. Presence of limited images necessitated extraction of patches and augmentation to boost...
Female Breast Neoplasms Deep Learning Humans Image Processing, Computer-Assisted Diagnosis, Differential
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Can low-frequency guided waves at the tibia paired with machine learning differentiate between healthy and osteopenic/osteoporotic subjects? A pilot study.

Ultrasonics Nov 30, 2018
PURPOSE: Axial transmission quantitative acoustics (ax-QA) has shown to be a promising tool for assessing bone health and properties in a safe, inexpensive, and portable manner. This study investigated the efficacy of low-frequency ax-QA measured at ...
Pilot Projects Radius Aged Humans Support Vector Machine Bone Diseases, Metabolic Aged, 80 and over Tibia Diagnosis, Differential Bone Density Absorptiometry, Photon Adult Ultrasonics Lumbar Vertebrae Osteoporosis Middle Aged Femur Neck Female
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A machine learning approach for distinguishing uterine sarcoma from leiomyomas based on perfusion weighted MRI parameters.

European journal of radiology Nov 13, 2018
PURPOSE: To propose a computer-assisted method for distinguishing uterine sarcoma from leiomyomas based on perfusion weighted magnetic resonance imaging (PWI).
Sensitivity and Specificity Humans Middle Aged Machine Learning Image Processing, Computer-Assisted Sarcoma Female Magnetic Resonance Imaging Uterine Neoplasms Reproducibility of Results Diagnosis, Differential Leiomyoma Adult
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Patch-based classification of thyroid nodules in ultrasound images using direction independent features extracted by two-threshold binary decomposition.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Oct 31, 2018
Ultrasound imaging of the thyroid gland is considered to be the best diagnostic choice for evaluating thyroid nodules in early stages, since it has been marked as cost-effective, non-invasive and risk-free. Computer aided diagnosis (CAD) systems can ...
Support Vector Machine Diagnosis, Differential Middle Aged Image Interpretation, Computer-Assisted Female Diagnosis, Computer-Assisted Ultrasonography Sensitivity and Specificity Thyroid Nodule Male Humans
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Ground Glass Lesions on Chest Imaging: Evaluation of Reported Incidence in Cancer Patients Using Natural Language Processing.

The Annals of thoracic surgery Oct 26, 2018
BACKGROUND: Ground glass opacities (GGOs) on computed tomography (CT) have gained significant recent attention, with unclear incidence and epidemiologic patterns. Natural language processing (NLP) is a powerful computing tool that collects variables ...
Humans Prognosis Follow-Up Studies Diagnosis, Differential Risk Factors Natural Language Processing Retrospective Studies Adenocarcinoma of Lung Texas Male Tomography, X-Ray Computed Middle Aged Female Incidence Reproducibility of Results
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A methodological approach for deep learning to distinguish between meningiomas and gliomas on canine MR-images.

BMC veterinary research Oct 22, 2018
BACKGROUND: Distinguishing between meningeal-based and intra-axial lesions by means of magnetic resonance (MR) imaging findings may occasionally be challenging. Meningiomas and gliomas account for most of the total primary brain neoplasms in dogs, an...
Image Interpretation, Computer-Assisted Meningioma Machine Learning Brain Neoplasms Animals Image Processing, Computer-Assisted Diagnosis, Differential Dogs Dog Diseases Glioma Magnetic Resonance Imaging Neural Networks, Computer
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Detecting drug-resistant tuberculosis in chest radiographs.

International journal of computer assisted radiology and surgery Oct 3, 2018
PURPOSE: Tuberculosis is a major global health threat claiming millions of lives each year. While the total number of tuberculosis cases has been decreasing over the last years, the rise of drug-resistant tuberculosis has reduced the chance of contro...
Machine Learning Tomography, X-Ray Computed Female Male Humans Neural Networks, Computer Tuberculosis, Multidrug-Resistant Probability Radiography, Thoracic Middle Aged Pilot Projects ROC Curve Diagnosis, Differential
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Comparison of radiomics machine-learning classifiers and feature selection for differentiation of sacral chordoma and sacral giant cell tumour based on 3D computed tomography features.

European radiology Oct 2, 2018
OBJECTIVE: We aimed to identify optimal machine-learning methods for preoperative differentiation of sacral chordoma (SC) and sacral giant cell tumour (SGCT) based on 3D non-enhanced computed tomography (CT) and CT-enhanced (CTE) features.
Humans Machine Learning Support Vector Machine Diagnosis, Differential Image Interpretation, Computer-Assisted Male Sacrum Linear Models Middle Aged Chordoma Spinal Neoplasms Retrospective Studies ROC Curve Giant Cell Tumors Tomography, X-Ray Computed Imaging, Three-Dimensional Female Adult
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