This project aims to investigate the effectiveness of four ML algorithms for the prediction of stroke. DATASET & SOURCE The data used for this project was gotten from Kaggle via thislink. The dataset consists of 5110 observations and 12 features that includes a binary target variable. That is,...
Using various statistical techniques and principal component analysis, we identify the most important factors for stroke prediction. We conclude that age, heart disease, average glucose level, and hypertension are the most important factors for detecting stroke in patients. Furthermore, a perceptron ...
Quantitative prediction of ischemic stroke tissue fate Probability-of-infarct maps were predicted using only acute stroke data from a separate experimental dataset, revealing the likelihood of future infarction. ... Qiang,Shen,Timothy,... - 《Nmr in Biomedicine》 被引量: 51发表: 2008年 Comparison...
First, the type and the severity of mesenteric ischemia were uncertain in this dataset. In addition, the brain image result, neurologic status and the severity of ischemic stroke were also lacking in this database. However, the validity of the nationwide dataset had been examined and documented ...
After applying Exploratory Data Analysis and Feature Engineering, the stroke prediction is done by using ML algorithms including Ensembling methods. 100% accuracy is reached in this notebook. The dataset is taken fromhttps://www.kaggle.com/datasets/jillanisofttech/brain-stroke-dataset. Also, the no...
Integrative polygenic risk prediction We investigated the risk prediction potential of stroke GWASs, alone and in combination with vascular-risk-trait GWASs, first in Europeans and East Asians, using ancestry-specific PGSs. PGSs were based on ancestry-specific and cross-ancestry GWAS summary statistics...
The analysis also yielded a significant main effect of Condition, χ2(1) = 17.54, p < .001, and no main effect of Group, χ2(1) = 5.56, p = .06. Fig. 2 Peak GFR as a function of weight condition for the control, LCVA, and RCVA group. Solid lines show ...
Defining core and penumbra in ischemic stroke: a voxel- and volume-based analysis of whole brain CT perfusion. Sci Rep. 2016;6:20932. doi:10.1038/srep20932 PubMedGoogle ScholarCrossref 27. Yu Y, Guo D, Lou M, Liebeskind D, Scalzo F. Prediction of hemorrhagic...
www.nature.com/scientificdata OPEN Received: 29 August 2017 Accepted: 11 December 2017 Published: 20 February 2018 Data Descriptor: A large, open source dataset of stroke anatomical brain images and manual lesion segmentations Sook-Lei Liew1,*, Julia M. Anglin1,*, Nick W. Banks1, Matt ...
The difference between the two prediction errors represents the mean decrease in accuracy for a specified variable; higher values represent greater variable importance [25, 26]. We also performed a principal components analysis on the scaled data at both speeds to allow visualization of the clusters...