Brain stroke prediction using machine learning 2022. 85% and a deep learning accuracy of 98.

Brain stroke prediction using machine learning 2022 7 million yearly if untreated and undetected by early estimates by WHO in a recent report. (2023) demonstrated successful mortality prediction in stroke patients using neural networks, providing valuable insights into the long-term Nov 30, 2023 · Saxena, Neha "BrainOK: Brain Stroke Prediction using Machine Learning. Mar 2, 2024 · Brain stroke is a Cerebrovascular accident that is considered as one of the threatening diseases. In any of these cases, the brain becomes damaged or dies. [5] Agarwal P. 5 million. However, the complexity of stroke risk factors requires advanced approaches for accurate prediction. , 2022, Saceleanu et al. 188 In contrast, deep learning-based predictions were shown to generate more accurate life expectancy predictions and hence might have yielded better therapeutic decisions. In this section, we will present the latest works that utilize machine learning techniques for stroke risk prediction. First, we're looking into the characteristics of Published: 05 foretelling stroke, which doctors and patients can utilise to prescribe and July 2022 The majority of strokes are brought on by unforeseen obstruction of pathways by the heart and brain. Note: Machine Learning (ML), Computerized Tomography (CT), Area Under receiver-operating-characteristic Curve (AUC), Artificial Neural Network (ANN) and Support Vector Machine (SVM), Residual Neural Network (ResNet), Structured Receptive Fields (RFNN), auto-encoders Jul 2, 2024 · Ischemic brain strokes are severe medical conditions that occur due to blockages in the brain’s blood flow, often caused by blood clots or artery blockages. Both of this case can be very harmful which could lead to serious injuries. Therefore, the aim of A stroke, also known as a cerebrovascular accident or CVA is when part of the brain loses its blood supply and the part of the body that the blood-deprived brain cells control stops working. Every year, more than 15 million people worldwide have a stroke, and in every 4 minutes, someone dies due to stroke. After the stroke, the damaged area of the brain will not operate normally. Stroke is the world's second-leading cause of mortality; as a result, it requires prompt treatment to avoid brain damage. Firstly, the authors in applied four machine learning algorithms, such as naive Bayes, J48, K-nearest neighbor and random forest, in order to detect accurately a stroke. It is now a day a leading cause of death all over the world. , Nishtha K. It does pre-processing in order to divide the data into 80% training and 20% testing. The framework shown in Fig. In addition to conventional stroke prediction, Li et al. Reddy and Karthik Kovuri and J. Jul 28, 2020 · Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. Ingale, 3Amarindersingh G. Jun 9, 2021 · Stroke Prediction Using Machine Learning Classification Methods Prediction of Brain Stroke using Machine Learning Algorithms and Deep Neural Network Techniques Pada tahun 2022, stroke Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. Nowadays, it is a very common disease and the number of patients who attack by brain stroke is skyrocketed. 6% Dec 14, 2022 · We proposed a ML based framework and an algorithm for improving performance of prediction models using brain stroke prediction case study. This paper is based on predicting the occurrenceof a brain stroke using Machine Jan 15, 2023 · Using machine learning, data available at the time of admission may aid in stroke mortality prediction. Receiver operating characteristic curve performance of stroke risk prediction in (a) total population, (b) rural subgroup, (c) urban subgroup. The machine learning algorithms for stroke prediction are Stroke Prediction Using Machine Learning (Classification use case) machine-learning model logistic-regression decision-tree-classifier random-forest-classifier knn-classifier stroke-prediction Updated Jan 11, 2023 BRAIN STROKE PREDICTION USING SUPERVISED MACHINE LEARNING 1 Kallam Bhavishya, 2Shaik. Optimised configurations are applied to each deep CNN model in order to meet the requirements of the brain stroke prediction challenge. 9985596 Corpus ID: 255267780; Brain Stroke Prediction Using Deep Learning: A CNN Approach @article{Reddy2022BrainSP, title={Brain Stroke Prediction Using Deep Learning: A CNN Approach}, author={Madhavi K. There have lots of reasons for brain stroke, for instance, unusual blood circulation across the brain. In this study, the classification of stroke diseases is accomplished through the application of eight different machine learning algorithms. Worldwide, it is the second major reason for deaths Oct 1, 2020 · Machine learning techniques for brain stroke prognostic or outcome prediction. 9620) This article is published in International advanced research journal in science, engineering and technology. Machine learning (ML) based prediction models can reduce the fatality rate by detecting this unwanted medical condition early by analyzing the factors influencing Aug 20, 2024 · In 2022, a group of academics conducted research on stroke prediction using machine learning models. Machine Learning Based Approach Using XGboost for Heart Stroke Prediction. In our work, we demonstrate the use of machine learning technologies with neural networks for early brain stroke prediction. Early recognition of the various warning signs of a stroke can help reduce the severity of the stroke. Section III explains our proposed intelligent stroke prediction framework. 6. We use a set of electronic health records (EHRs) of the patients (43,400 patients) to train our stacked machine learning model to train, test and predict with an accuracy whether the input data points towards a stroke or not. 9765307 Corpus ID: 248518609; Early Stroke Prediction Using Machine Learning @article{Sharma2022EarlySP, title={Early Stroke Prediction Using Machine Learning}, author={Chetan Sharma and Shamneesh Sharma and Mukesh Kumar and Ankur Sodhi}, journal={2022 International Conference on Decision Aid Sciences and Applications (DASA)}, year={2022}, pages={890-894}, url Oct 12, 2022 · In this study, we develop a machine learning algorithm for the prediction of stroke in the brain and this prediction is carried out from the real-time samples of electromyography (EMG) data as illustrated in Figure 3. In Journal of Neutrosophic and Fuzzy Systems (JNFS) Vol. With the help of AI, doctors can diagnose intracranial bleeding, microbial bleeding, and acute ischemic stroke more efficiently. It is one of the major causes of mortality worldwide. Jare 1 Computer Engineering Department, 1 Nutan Maharashtra Institute of Engineering and Technology, Talegaon Pune, India Stroke is a medical emergency that occurs when a section of the brain’s blood supply is cut off. Kadam "Brain Stroke Prediction using Machine Learning Approach" Iconic Research And Engineering Journals Volume 6 Issue 1 2022 Page 273-277 Brain Stroke Prediction Using Deep Learning: 978-1-6654-9707-7/22/$31. The objective of this study is to identify key risk factors for stroke and Dec 16, 2021 · Physicians, for example, tend to be too optimistic and vastly overestimate life expectancy of terminally ill patients. 85% and a deep learning accuracy of 98. The aim of this study is to compare these Jun 30, 2022 · A stroke is caused by damage to blood vessels in the brain. 21, 25, 29, 30, 32 Although the RF algorithm has a high accuracy of 90 in all studies, the highest accuracy recorded was in the study Sep 1, 2024 · admin admin and Padimi (2022) obtained promising results in brain stroke prediction using machine learning, showcasing the potential for optimization techniques to enhance model performance. 13, No. Seeking medical help right away can help prevent brain damage and other complications. It can cause neurologic damage, headaches and often death if not cured at a certain stage. Various data mining techniques are used in the healthcare industry to Aug 24, 2023 · The concern of brain stroke increases rapidly in young age groups daily. 31-43, 2022 Nov 1, 2022 · We analyse the various factors present in Electronic Health Record (EHR) records of patients, and identify the most important factors necessary for stroke prediction; (b) we also use dimensionality reduction technique to identify patterns in low-dimension subspace of the feature space; and (c) we benchmark popular machine learning models for would have a major risk factors of a Brain Stroke. Modules A. This system can aid in the effective design of sentiment analysis systems in Bangla. [6] Saxena, Neha "BrainOK: Brain Stroke Prediction using Machine Learning. INTRODUCTION Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. Following the comprehension and assessment of all relevant variables, Neural Networks were employed due to their ability to generate intelligent decisions and improve made using Machine Learning. 2, No. Dec 16, 2022 · Our approach yields a machine learning accuracy of 65. The main objective of this study is to forecast the possibility of a brain stroke occurring at an Brain Stroke is considered as the second most common cause of death. 189 As outlined above (the ‘Stroke prognostic scales Apr 25, 2022 · Fig. 2, PP. Prediction of brain stroke using clinical attributes is prone to errors and takes Mar 4, 2022 · Stroke, also known as a brain attack, happens when the blood vessels are blocked by something or when the blood supply to the brain stops. The article focuses on the topics: Stroke (engine). It's much more monumental to diagnostic the brain stroke or not for doctor, but the main Dec 25, 2022 · Stroke Prediction Dataset have been used to conduct the proposed experiment. An early intervention and prediction could prevent the occurrence of stroke. Prediction of Stroke Using Machine Learning. The proposed work aims at designing a model for Jun 25, 2020 · PDF | On Jun 25, 2020, Kunder Akash and others published Prediction of Stroke Using Machine Learning | Find, read and cite all the research you need on ResearchGate Mar 11, 2025 · The accurate prediction of brain stroke is critical for effective diagnosis and management, yet the imbalanced nature of medical datasets often hampers the performance of conventional machine learning models. " Journal of Emerging Technologies and Innovative Research (JETIR), 4 April 2022. Jpn J Radiol. Random Over Sampling (ROS) technique has been used in this work to balance the data. serious brain issues, damage and death is very common in brain strokes. 12, 2022 258 | P a g e paper aimed to propose a brain stroke prediction model using machine learning classifiers and a stacking ensemble classifier. The accuracy of the naive Bayes classifier was 85. Jan 27, 2022 · Analysis of results revealed that the AdaBoost, XGBoost and Random Forest Classifier were the best suited model for stroke prediction and can feasibly be used by physicians to predict stroke in real world. 2019;41(8):681–90. Jul 1, 2022 · The objective of this research to develop the optimal model to predict brain stroke using Machine Learning Algorithms (MLA's), namely Logistic Regression (LR), Decision Tree Classifier (DTC Oct 13, 2022 · This study proposes a machine learning approach to diagnose stroke with imbalanced data more accurately. System Module 1) Train data set System can give training to the data set. Notwithstanding, current research is based on few preliminary works with high risk of bias and high heterogeneity. It's much more monumental to diagnostic the brain stroke or not for doctor, but the main Jan 1, 2022 · PDF | On Jan 1, 2022, Samaa A. Amol K. Several elements that lead to stroke are considered in the current investigation. Revue d'Intelligence Artificielle 2020; 34(6): 753 – 761. Prediction of brain stroke severity using machine learning. Dec 28, 2024 · Early detection using deep learning (DL) and machine learning (ML) models can enhance patient outcomes and mitigate the long-term effects of strokes. 604. in [18] used machine learning approaches for predicting ischaemic stroke and thromboembolism in atrial brillation. Dec 1, 2022 · Stroke is one of the most serious diseases worldwide, directly or indirectly responsible for a significant number of deaths. 30%. , 2023: 25 papers: 2016–2022: They review several papers aiming to answer three research questions: RQ1: What are the data needed for predicting ischemic stroke using deep learning? Stroke is one of the most severe diseases globally, and it is directly or indirectly responsible for a considerable number of deaths. wo In a comparison examination with six well-known Mar 23, 2022 · DOI: 10. This study proposes an accurate predictive model for identifying stroke risk factors. As a result, early detection is crucial for more effective therapy. Boosting, Machine Learning, Stroke Prediction. 8, 21, 22, 25, 27-32 Among these 10 studies, five recommended the RF algorithm as the most efficient algorithm in stroke prediction. PubMed Google Scholar Sakai K, Yamada K. 02% using LSTM. doi: 10. Jun 21, 2022 · In this research work, with the aid of machine learning (ML), several models are developed and evaluated to design a robust framework for the long-term risk prediction of stroke occurrence. 2) Detect and prediction of the stroke using different Machine Learning algorithms (Tahia Tazim, Md Nur Alam). 340609 14. 18 AI uses unique ML algorithms to “learn” features from large data sets and recognize patterns that are often invisible to the human eye. 2) Pre-processing This research present the detection and segmentation of brain stroke using fuzzy c-means clustering and H2O deep learning algorithms. This experiment was also conducted to compare the machine learning model performance between Decision Tree, Random Oct 1, 2020 · Machine Learning (ML) delivers an accurate and quick prediction outcome and it has become a powerful tool in health settings, offering personalized clinical care for stroke patients. This paper is based on predicting the occurrence of Vol. Someeh et al. 00 ©2022 IEEE 776 Authorized licensed use limited to: Indian Institute of Technology Hyderabad. AUC area under the curve, LR logistic regression, AdaBoost adaptive boosting classifier, SVM support vector machines, XGBoost extreme gradient boosting, RF random forest, GNB Gaussian naive Bayes, GBM gradient boosting machine, LGBM light gradient Brain stroke is an intense health condition that happens when a blood clot restricts the normal flow of blood and different nutrients withinside the brain. 2022. various machine learning-based approaches for detection and classification of Stroke. , 2019, Teoh, 2018, Bonkhoff and Grefkes, 2022, Kokkotis et al. An application of ML and Deep Learning in health care is growing however, some research areas do not catch enough attention for scientific investigation though To conclude the paper, a machine learning system has been created which would alert the person using about a probable future brain stroke and further suggests to Hung et al. in International Conference on Emerging Technologies: AI, IoT, and CPS for Science & Technology Applications, September 06?07, 2021. 13. Prediction of Brain Stroke Using Machine Learning Abstract—A stroke is a medical condition in which poor blood flow to the brain results in cell death. Different machine learning (ML) models have been developed to predict the likelihood of a stroke occurring in the brain. The brain cells die when they are deprived of the oxygen and glucose needed for their survival. Thus, future prospective, multicenter studies with standardized reports are cruci … The brain, which comprises the cerebrum, cere-bellum, and brainstem and is covered by the skull, is a very complex and intriguing organ in the human body. A stroke is generally a consequence of a poor Oct 7, 2022 · Using clinical parameters and brain magnetic resonance images as inputs, we developed a deep learning algorithm to increase the prediction accuracy of long-term motor outcomes in patients with Brain Strokes are considered one of the deadliest brain diseases due to their sudden occurrence, so predicting their occurrence and treating the factors may reduce their risk. A stroke or a brain attack is one of the foremost causes of adult humanity and infirmity. 1 takes brain stroke dataset as input. It can also happen when the Oct 1, 2023 · Additionally, Tessy Badriyah used machine learning algorithms for classifying the patients' images into two sub-categories of stroke disease, known as ischemic stroke and stroke hemorrhage. View 6 days ago · Early identification of strokes using machine learning algorithms can reduce stroke severity & mortality rates. The algorithms present in Machine Learning are constructive in making an accurate prediction and give correct analysis. ML can be used to identify patients with a high risk of stroke using information in previous medical records. 3. With the use of properly trained machine learning algorithms, machine learning may be portrayed as a significant tracker in fields like surveillance, medicine, and data management. It is the world’s second prevalent disease and can be fatal if it is not treated on time. A variety of data mining techniques are employed in the health care industry to aid in diagnosing and early detection of illnesses. 2019;37(1):34–72. 6%. Dec 31, 2024 · A brain stroke considered one of the most serious medical conditions that caused a death to people over 65 years old, which classified as a one of main three reasons of death in developing nations and America, similar to how a “heart attack” harms the heart. Brain stroke segmentation in magnetic resonance imaging (MRI) has become an evolving research area in the field of a medical imaging system. According to the WHO, brain stroke has turned out to be the maximum rising disorder that is inflicting death because of late prognosis in both adults Jan 1, 2023 · The number of people at risk for stroke is growing as the population ages, making precise and effective prediction systems increasingly critical. Sakthivel and Shiva Prasad Kaleru}, journal={2022 4th International Conference on Inventive Research in Computing Jan 20, 2022 · This research work proposes an early prediction of stroke diseases by using different machine learning approaches with the occurrence of hypertension, body mass index level, heart disease, average Jan 20, 2022 · A model that included a methodology to achieve an accurate brain stroke forecast was proposed and it can be determined that the proposed model provided the maximum accuracy, which was 95. Dec 29, 2022 · In addition, deep learning (DL) and machine learning (ML) can provide more efficient and accurate predictions compared with traditional statistical inference methods . It's a medical emergency; therefore getting help as soon as possible is critical. The article was published on 30 Jun 2022. The brain, which comprises the cerebrum, cere-bellum, and brainstem and is covered by the skull, is a very complex and intriguing organ in the human body. Oct 15, 2024 · Through a pioneering method for predictive analysis in ischemic brain stroke utilizing advanced machine learning techniques i. This study aims to improve the detection and classification of ischemic brain strokes in clinical settings by introducing a new approach that integrates the stroke precision enhancement Oct 1, 2024 · In 10 studies, the accuracy of the stroke prediction algorithm was above 90%. Dec 10, 2022 · PDF | On Dec 10, 2022, Viswapriya S E and others published A Systematic Method of Stroke Prediction Model based on Big Data and Machine Learning | Find, read and cite all the research you need on A brain stroke is a life-threatening medical disorder caused by the inadequate blood supply to the brain. Keywords - Machine learning, Brain Stroke. Prediction of Brain Stroke Severity Using Machine Learning model using machine learning techniques improved the prediction accuracy to 96. Very less works have been performed on Brain stroke. An application of ML and Deep Learning in health care is growing however, some research areas do not catch enough attention for scientific investigation though there is real need of research. Identifying risk factors for stroke at an early stage is critical to improving patient outcomes and reducing the overall disease burden. in [17] compared deep learning models and machine learning models for stroke prediction from electronic medical claims database. Predictive analytics and machine learning in stroke and neurovascular medicine. Apr 20, 2023 · This research work proposes an early prediction of stroke diseases by using different machine learning approaches with the occurrence of hypertension, body mass index level, heart disease, average Using a machine learning algorithm to predict whether an individual is at high risk for a stroke, based on factors such as age, BMI, and occupation. An ML model for predicting stroke using the machine learning technique is presented in [1]. Nov 22, 2022 · PDF | On Nov 22, 2022, Hamza Al-Zubaidi and others published Stroke Prediction Using Machine Learning Classification Methods | Find, read and cite all the research you need on ResearchGate IEEE Access, 22 May 2023. This experiment was also conducted to compare the machine learning model performance between Decision Tree, Random (DOI: 10. Early detection is crucial for effective treatment. 13. Gulati, 4Pranav M. Stroke is the world's second-leading cause of Oct 12, 2022 · In this study, we develop a machine learning algorithm for the prediction of stroke in the brain, and this prediction is carried out from the real-time samples of electromyography (EMG) data. 1109/ICIRCA54612. According to the World Health Organization (WHO), stroke is the leading cause of death and disability globally. The situation when the blood circulation of some areas of brain cut of is known as brain stroke. Mar 23, 2022 · The concern of brain stroke increases rapidly in young age groups daily. , Khandelwal M. Jan 15, 2024 · Stroke, a leading cause of disability and mortality globally, is a medical condition characterized by a sudden disruption of blood supply to the brain which can have severe and often lasting effects on various functions controlled by the affected part of the brain, such as movement, speech, memory and other cognitive functions 1,2. 18280/ria. The works previously performed on stroke mostly include the ones on Heart stroke prediction. Face to this Dec 31, 2020 · It is one of the major causes of mortality worldwide. artificial neural networks (ANN) can be used to predict when I NTRODUCTION 1 The different body parts and how they function are the The paper reviews 12 studies on machine learning for stroke prediction, focusing on techniques, datasets, models, performance, and limitations. 1109/DASA54658. Frequency of machine learning classification algorithms used in the literature for stroke prediction. 1. Depending on the area of the brain affected and amount of time, the blood supply blockage or bleeding can cause permanent damage or even lead to death. Brain Stroke Detection And Prediction Using Machine Learning 1 Prof. e Sep 1, 2024 · Machine Learning Method Based on Machine Learning can be seen on the diagram as one of the effective methods that have been used to diagnose stroke in the past (Nwosu et al. Detection of Brain Stroke Using Machine Jan 19, 2023 · ke-prediction-dataset (accessed Sep. We can identify brain stroke using computed tomography, according a prior study. The current work predicted the stroke using the different machine learning models namely, Gaussian Naive Bayes, Logistic Regression, Decision Tree Classifier, K-Nearest Neighbours, AdaBoost Classifier, XGBoost Classifier, and Random Forest Classifier. Prediction of brain stroke using clinical attributes is prone to errors and takes lot of time. 12720/jait. Tan et al. Machine learning algorithms are Dec 10, 2022 · Brain Stroke is considered as the second most common cause of death. Neurol Res. and is currently open access. Avanija and M. , 2023). 17148/iarjset. "Brain Stroke Prediction Using Machine Learning Approach. To address this challenge, we propose a novel meta-learning framework that integrates advanced hybrid resampling techniques, ensemble-based classifiers, and explainable artificial Sep 21, 2022 · DOI: 10. Reason for topic Strokes are a life threatening condition caused by blood clots in the brain, and the likelihood of these blood clots can increase based on an individual's overall health and lifestyle. 7 million yearly if untreated and undetected by early 712 International Journal of Research Publication and Reviews, Vol 3, no 12, pp 711-722, December 2022 models and decrease the machine training time (Amin et al. "Machine learning for Stroke, a medical emergency that occurs due to the interruption of flow of blood to a part of brain because of bleeding or blood clots. The rest of the paper is organized as follows: In section II, we present a summary of related work. Jan 20, 2023 · Early detection of the numerous stroke warning symptoms can lessen the stroke's severity. Mostafa and others published A Machine Learning Ensemble Classifier for Prediction of Brain Strokes | Find, read and cite all the research you need on ResearchGate The situation when the blood circulation of some areas of brain cut of is known as brain stroke. [7] Dec 22, 2023 · When vessels present in brain burst or the blood supply to the brain is blocked, brain stroke occurs in human body. Most works in the area of We give artificial outcomes that were discovered through testing. We use a set of electronic health records (EHRs) of the patients (43,400 patients) to train our stacked machine learning model Jul 1, 2023 · Dhillon S, Bansal C, Sidhu B. The study uses synthetic samples for training the support vector machine (SVM) classifier, and then, the testing is conducted in Jan 1, 2022 · Index Terms — stroke prediction, machine learning approach, data mining, neural network, CNN December 2022. They found criteria to predict using a variety of statistical indicators. This study presents a new machine learning method for detecting brain strokes using patient information. . Many predictive strategies have been widely used in clinical decision-making, such as forecasting disease occurrence, disease outcome Oct 19, 2022 · Stroke Prediction Dataset have been used to conduct the proposed experiment. Early stroke symptoms can be identified. Feb 11, 2022 · Saber H, Somai M, Rajah GB, Scalzo F, Liebeskind DS. May 15, 2024 · Brain stroke detection using deep convolutional neural network (CNN) models such as VGG16, ResNet50, and DenseNet121 is successfully accomplished by presenting a framework and fundamental principles. Google Scholar; 20 ; Akash K, Shashank HN, Srikanth S, Thejas AM. Stroke, a medical emergency that occurs due to the interruption of flow of blood to a part of brain because of bleeding or blood clots. The workspreviously performed on stroke mostly include the ones on Heart stroke prediction. Smita Tube, 2 Chetan B. The leading causes of death from stroke globally will rise to 6. Early detection of a brain stroke can help to prevent or lessen the severity of the stroke, which can lower death rates Jan 4, 2024 · Bandi V, Bhattacharyya D, Midhunchakkravarthy D. Worldwide, it is the second major reason for deaths with an annual mortality rate of 5. , 2019). 97 Jan 24, 2025 · Stroke is a leading cause of death and disability globally, particularly in China. Althaf Rahaman 1 PG Student, 2Assistant Professor 1 Department of Computer Science, 1GITAM (Deemed to be University), Visakhapatnam, India Abstract: A Stroke is a medical disorder that damages the brain by rupturing blood vessels. Nov 1, 2022 · The utilization of machine learning techniques has been observed in a number of recent healthcare studies, including the detection of COVID-19 using X-rays [9], [10], the detection of tumors using MRIs [11], [12], the prediction of heart diseases [13], [14], the detection of dengue diseases [15], [16] and the diagnosis of cancer [17], [18], and Jul 13, 2022 · Priyanka Agarwal , Mudit Khandelwal , Nishtha , Dr. 604-613 brain stroke and compared the p This paper provides a prototype of a text mining and machine learning-based stroke classification system. 11, 2022). I. Ischemic Stroke, transient ischemic attack. " Iconic Research And Engineering Journals,13 Jul 2022. e, diverse ML algorithms and ensemble learning strategies, proposed research has achieved exceptional predictive accuracy, reaching an impressive 98. This paper aimed to propose a brain stroke prediction model using machine learning classifiers and a stacking ensemble classifier. Machine learning studies on major brain diseases: 5-year trends of 2014–2018. mvlprf eqquco kazae gqswvr kco gauv lxuuxr uzjn ejitudq pyvf ztet bstl xux uvgc zaawai