AIMC Topic: Diagnosis, Differential
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Artificial Intelligence System Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI.
Radiology
Apr 7, 2020
Background Although artificial intelligence (AI) shows promise across many aspects of radiology, the use of AI to create differential diagnoses for rare and common diseases at brain MRI has not been demonstrated. Purpose To evaluate an AI system for ...
Radiomics in gliomas: clinical implications of computational modeling and fractal-based analysis.
Neuroradiology
Apr 6, 2020
Radiomics is an emerging field that involves extraction and quantification of features from medical images. These data can be mined through computational analysis and models to identify predictive image biomarkers that characterize intra-tumoral dyna...
Multivariate patterns of EEG microstate parameters and their role in the discrimination of patients with schizophrenia from healthy controls.
Psychiatry research
Apr 6, 2020
Quasi-stable electrical fields in the EEG, called microstates carry information on the dynamics of large scale brain networks. Using machine learning techniques, we explored whether abnormalities in microstates can be used to classify patients with s...
Alzheimer's disease, mild cognitive impairment, and normal aging distinguished by multi-modal parcellation and machine learning.
Scientific reports
Mar 25, 2020
A 360-area surface-based cortical parcellation is extended to study mild cognitive impairment (MCI) and Alzheimer's disease (AD) from healthy control (HC) using the joint human connectome project multi-modal parcellation (JHCPMMP) proposed by us. We ...
Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy.
Radiology
Mar 19, 2020
Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginning of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest CT. Purpose To develop a fully automatic framework to...
Pneumonia, Viral
Coronavirus Infections
COVID-19 Testing
Humans
Community-Acquired Infections
Artificial Intelligence
Clinical Laboratory Techniques
Pandemics
Betacoronavirus
ROC Curve
COVID-19
Imaging, Three-Dimensional
Adult
Diagnosis, Differential
Retrospective Studies
Sensitivity and Specificity
Radiographic Image Interpretation, Computer-Assisted
Tomography, X-Ray Computed
Male
Female
Middle Aged
SARS-CoV-2
Deep Learning
Aged
Identifying predictive features of autism spectrum disorders in a clinical sample of adolescents and adults using machine learning.
Scientific reports
Mar 18, 2020
Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). ...
Machine Learning Diagnostic Modeling for Classifying Fibromyalgia Using B-mode Ultrasound Images.
Ultrasonic imaging
Mar 16, 2020
Fibromyalgia (FM) diagnosis remains a challenge for clinicians due to a lack of objective diagnostic tools. One proposed solution is the use of quantitative ultrasound (US) techniques, such as image texture analysis, which has demonstrated discrimina...
Artificial Intelligence based Models for Screening of Hematologic Malignancies using Cell Population Data.
Scientific reports
Mar 16, 2020
Cell Population Data (CPD) provides various blood cell parameters that can be used for differential diagnosis. Data analytics using Machine Learning (ML) have been playing a pivotal role in revolutionizing medical diagnostics. This research presents ...
Differentiation of distal ureteral stones and pelvic phleboliths using a convolutional neural network.
Urolithiasis
Feb 27, 2020
The objectives were to develop and validate a Convolutional Neural Network (CNN) using local features for differentiating distal ureteral stones from pelvic phleboliths, compare the CNN method with a semi-quantitative method and with radiologists' as...
Separation of HCM and LQT Cardiac Diseases with Machine Learning of Ca2+ Transient Profiles.
Methods of information in medicine
Feb 20, 2020
BACKGROUND: Modeling human cardiac diseases with induced pluripotent stem cells not only enables to study disease pathophysiology and develop therapies but also, as we have previously showed, it can offer a tool for disease diagnostics. We previousl...
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