ArticleScientific reports2017
Prediction of infarction volume and infarction growth rate in acute ischemic stroke.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Predicting infarction growth rate II using ANFIS-based binary particle swarm optimization technique in ischemic stroke.MethodsX · 2023Article
- iMIGS: An innovative AI based prediction system for selecting the best patient-specific glaucoma treatment.MethodsX · 2023Article
- Infarct growth patterns may vary in acute stroke due to large vessel occlusion and recanalization with endovascular therapy.European radiology · 2020Article
- Novel Estimation of Penumbra Zone Based on Infarct Growth Using Machine Learning Techniques in Acute Ischemic Stroke.Journal of clinical medicine · 2020Article
- Borneol for Regulating the Permeability of the Blood-Brain Barrier in Experimental Ischemic Stroke: Preclinical Evidence and Possible Mechanism.Oxidative medicine and cellular longevity · 2019Review
- Factors that Can Help Select the Timing for Decompressive Hemicraniectomy for Malignant MCA Stroke.Translational stroke research · 2018Article
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9 authors.
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Abstract
The prediction of infarction volume after stroke onset depends on the shape of the growth dynamics of the infarction. To understand growth patterns that predict lesion volume changes, we studied currently available models described in literature and compared the models with Adaptive Neuro-Fuzzy Inference System [ANFIS], a method previously unused in the prediction of infarction growth and infarction volume (IV). We included 67 patients with malignant middle cerebral artery [MMCA] stroke who underwent decompressive hemicraniectomy. All patients had at least three cranial CT scans prior to the surgery. The rate of growth and volume of infarction measured on the third CT was predicted with ANFIS without statistically significant difference compared to the ground truth [P = 0.489]. This was not possible with linear, logarithmic or exponential methods. ANFIS was able to predict infarction volume [IV3] over a wide range of volume [163.7-600 cm
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