Development of an intelligent decision support system for ischemic stroke risk assessment in a population-based electronic health record database - Fig 2

Performance of the deep learning model for predicting 3 year stroke occurrence in (A) testing dataset 1 and (B) testing dataset 2.</p

The 3 year and 8 year stroke rate of patients in the 5 risk categories in the testing datasets.

The 3 year and 8 year stroke rate of patients in the 5 risk categories in the testing datasets.</p

Characteristics of development and testing datasets.

Characteristics of development and testing datasets.</p

Performance of currently available stroke risk assessment scores and the deep learning model.

Performance of currently available stroke risk assessment scores and the deep learning model.</p

A 48-Week, Multicenter, Open-Label, Observational Study, Evaluating Oral Rivastigmine in Patients with Mild-to-Moderate Alzheimer’s Disease in Taiwan

Full copyright for enhanced digital features is owned by the authors. Article full text The full text of this article can be found here. Provide enhanced digital features for this article If you are an author of this publication and would like to provide additional enhanced digital features for your article then please contact [email protected]. The journal offers a range of additional features designed to increase visibility and readership. All features will be thoroughly peer reviewed to ensure the content is of the highest scientific standard and all features are marked as ‘peer reviewed’ to ensure readers are aware that the content has been reviewed to the same level as the articles they are being presented alongside. Moreover, all sponsorship and disclosure information is included to provide complete transparency and adherence to good publication practices. This ensures that however the content is reached the reader has a full understanding of its origin. No fees are charged for hosting additional open access content. Other enhanced features include, but are not limited to: • Slide decks • Videos and animations • Audio abstracts • Audio slides</p

Development of an intelligent decision support system for ischemic stroke risk assessment in a population-based electronic health record database - Fig 3

Sensitivity and specificity of the DNN model for predicting 3 year stroke occurrence in different testing time periods under (A) the high specificity operating point and (B) the high sensitivity operating point.</p

Attributable risk difference of ROAF in acute strokes with unilateral high-grade cervical internal carotid stenosis/occlusion and intracranial stenosis.

<p>CI, confidence interval; no., number; OR, odds ratio; ROAF, reversed ophthalmic artery flow.</p

Functional outcomes of patients with acute stroke in the presence of ROAF or intracranial stenosis.

<p>Patients with acute stroke were divided into 4 subgroups: severe intracranial stenosis (>50%) and forward OA, severe intracranial stenosis (>50%) and reversed OA, mild intracranial stenosis (≤50%) and forward OA, and mild intracranial stenosis (≤50%) and reversed OA.ROAF and less intracranial stenosis are good predictors for acute stroke outcomes. mRS, modified Rankin Scale; NIHSS, National Institutes of Health Stroke Scale; no., number; OA, ophthalmic artery; <i>*</i>p = p value for trend. Statistically significant differences were evaluated using Fisher's exact test for categorical variables between the tested groups and Mantel–Haenszel extension tests for trend analyses. ^ap<0.05 vs. forward OA and intracranial stenosis >50%; ^bp<0.01 vs. forward OA and intracranial stenosis >50%; ^cp<0.05 vs. reversed OA and intracranial stenosis >50%; ^dp<0.01 vs. reversed OA and intracranial stenosis >50%.</p

Study patient selection.

<p>FOAF, forward ophthalmic artery flow; MR, magnetic resonance; ROAF, reversed ophthalmic artery flow; EC-IC bypass, extracranial–intracranial bypass.</p

Age-adjusted analysis of clinical characteristics in acute strokes with unilateral high-grade cervical internal carotid stenosis or occlusion.

<p>AF, atrial fibrillation; CAD, coronary artery disease; CI, confidence interval; DM, diabetes mellitus; F, female; M, male; NIHSS, National Institutes of Health Stroke Scale; no, number; OA, ophthalmic artery; OR, odds ratio. Statistically significant differences for categorical variables between tested groups were evaluated using age-adjusted logistic analysis.</p