Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach

2018 ◽  
Vol 48 (1) ◽  
pp. 198-204 ◽  
Author(s):  
Valeria Romeo ◽  
Simone Maurea ◽  
Renato Cuocolo ◽  
Mario Petretta ◽  
Pier Paolo Mainenti ◽  
...  
Keyword(s):  
Machine Learning ◽  
Texture Analysis ◽  
Learning Approach ◽  
Machine Learning Approach

scholarly journals Validation of a Derived International Patient Severity Algorithm to Support COVID-19 Analytics from Electronic Health Record Data

2020 ◽  
Author(s):  
Jeffrey G Klann ◽  
Griffin M Weber ◽  
Hossein Estiri ◽  
Bertrand Moal ◽  
Paul Avillach ◽  
...  
Keyword(s):  
Machine Learning ◽  
Chart Review ◽  
Learning Approach ◽  
Learning Approaches ◽  
Electronic Health Record Data ◽  
Icu Admission ◽  
Machine Learning Approach ◽  
Proxy Measure ◽  
Definition Of

AbstractIntroductionThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE) includes hundreds of hospitals internationally using a federated computational approach to COVID-19 research using the EHR.ObjectiveWe sought to develop and validate a standard definition of COVID-19 severity from readily accessible EHR data across the Consortium.MethodsWe developed an EHR-based severity algorithm and validated it on patient hospitalization data from 12 4CE clinical sites against the outcomes of ICU admission and/or death. We also used a machine learning approach to compare selected predictors of severity to the 4CE algorithm at one site.ResultsThe 4CE severity algorithm performed with pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of single code categories for acuity were unacceptably inaccurate - varying by up to 0.65 across sites. A multivariate machine learning approach identified codes resulting in mean AUC 0.956 (95% CI: 0.952, 0.959) compared to 0.903 (95% CI: 0.886, 0.921) using expert-derived codes. Billing codes were poor proxies of ICU admission, with 49% precision and recall compared against chart review at one partner institution.DiscussionWe developed a proxy measure of severity that proved resilient to coding variability internationally by using a set of 6 code classes. In contrast, machine-learning approaches may tend to overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold standard outcomes, possibly due to pandemic conditions.ConclusionWe developed an EHR-based algorithm for COVID-19 severity and validated it at 12 international sites.

scholarly journals A machine learning approach on multiscale texture analysis for breast microcalcification diagnosis

2020 ◽  
Vol 21 (S2) ◽  
Author(s):  
Annarita Fanizzi ◽  
Teresa M. A. Basile ◽  
Liliana Losurdo ◽  
Roberto Bellotti ◽  
Ubaldo Bottigli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Texture Analysis ◽  
Learning Approach ◽  
Machine Learning Approach ◽  
Breast Microcalcification

Application of a machine learning approach to characterization of liver function using 99mTc-GSA SPECT/CT

2021 ◽  
Author(s):  
Masatoyo Nakajo ◽  
Megumi Jinguji ◽  
Atsushi Tani ◽  
Daisuke Hirahara ◽  
Hiroaki Nagano ◽  
...  
Keyword(s):  
Machine Learning ◽  
Liver Function ◽  
Learning Approach ◽  
Machine Learning Approach

scholarly journals Automatic Characterization of Exploitable Faults: A Machine Learning Approach

2019 ◽  
Vol 14 (4) ◽  
pp. 954-968 ◽  
Author(s):  
Sayandeep Saha ◽  
Dirmanto Jap ◽  
Sikhar Patranabis ◽  
Debdeep Mukhopadhyay ◽  
Shivam Bhasin ◽  
...  
Keyword(s):  
Machine Learning ◽  
Learning Approach ◽  
Machine Learning Approach
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