Brain stroke prediction using machine learning pdf In this paper, we present an advanced stroke detection algorithm Brain Stroke Prediction Using Machine Learning and Data Science VEMULA GEETA1, T. artificial neural networks (ANN) can be used to predict when I NTRODUCTION 1 The different body parts and how they function are the Keywords—Accuracy, Data preprocessing, Machine Learning, Prediction,Stroke I. 5 Hours 2018 Expert SystemDetect Dec 28, 2024 · Failure to predict stroke promptly may lead to delayed treatment, causing severe consequences like permanent neurological damage or death. Hung et al. The study uses synthetic samples for training the support vector machine (SVM) classifier and then the testing is conducted in real-time samples. Decision tree. Padmavathi,P. Overall, this observe demonstrates the effectiveness of A-Tuning Ensemble machine learning in stroke prediction and achieves excellent outcomes. The works previously performed on stroke mostly include the ones on Heart stroke prediction. 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. made using Machine Learning. 1 takes brain stroke dataset as input. The key components of the approaches used and results obtained are that among the five different classification algorithms used Naïve Bayes Jun 30, 2022 · The results obtained show that Deep Learning models outperformed the Machine Learning models, moreover the DenseNet-121 provided the best results for brain stroke prediction with an accuracy of 96%. Nov 29, 2024 · The document describes a proposed intelligent career guidance system using machine learning. Dec 1, 2022 · This is to certify that the project entitled “ Brain Stroke Prediction by Using Machine Learning ” is a bonafide record of the work done by S. 5 million. The brain cells die when they are deprived of the oxygen and glucose needed for their survival. Implementing a combination of statistical and machine-learning techniques, we explored how BRAIN STROKE PREDICTION BY USING MACHINE LEARNING S. Face to this Our ML model uses dataset to predict whether the person has any chances of getting stroke the parameters that are considered to predict stroke are gender, age, disease, smoking status, Cystatin-c , MMP10, Tau Our dataset focuses on major factors which has causes of brain stroke. Brain Stroke is a long-term disability disease that occurs all over the world and is the leading cause of death. pdf), Text File (. Jun 12, 2020 · While machine learning prediction models for stroke mortality exhibit commendable accuracy [2], concerns have emerged regarding their practical utility and clinical application, particularly when We give artificial outcomes that were discovered through testing. in [18] used machine learning approaches for predicting ischaemic stroke and thromboembolism in atrial brillation. Jun 9, 2021 · This research article aims apply Data Analytics and use Machine Learning to create a model capable of predicting Stroke outcome based on an unbalanced dataset containing information about 5110 Dec 16, 2022 · PDF | The situation when the blood circulation of some areas of brain cut of is known as brain stroke. SaiRohit Abstract A stroke is a medical condition in which poor blood flow to the brain results in cell death. International Journal for Research in Engineering Application & Management , 07 (03), 262–268. In the data preprocessing module, the 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 Interpretable Stroke Risk Prediction Using Machine Learning Algorithms 649. After a stroke, the affected brain areas fail to function. When part of the brain does not receive sufficient blood flow for functioning a brain stroke strikes a person. An ML model for predicting stroke using the machine 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. ARUNA VARANASI3, ADIMALLA PAVAN KUMAR4, BILLA CHANDRA KIRAN5, V. [4] “Prediction of stroke thrombolysis outcome using CT brain machine learning” - Paul Bentley, JebanGanesalingam, AnomaLalani, CarltonJones, KateMahady, SarahEpton, PaulRinne, PankajSharma, OmidHalse, AmrishMehta, DanielRueckert - Clinical records and CT brains of 116 acute ischemic stroke patients Prediction of Brain Stroke Using Machine Learning - Free download as PDF File (. The system consists of the following key components: Key Components: The architecture is composed of essential modules, each performing critical functions in stroke prediction, and the paper’s contribution lies in preparing the dataset using machine learning algorithms. 5 algorithm, Principal Component [4] “Prediction of stroke thrombolysis outcome using CT brain machine learning” - Paul Bentley, JebanGanesalingam, AnomaLalani, CarltonJones, KateMahady, SarahEpton, PaulRinne, PankajSharma, OmidHalse, AmrishMehta, DanielRueckert - Clinical records and CT brains of 116 acute ischemic stroke patients of the major risk factors for stroke. One of its primary applications is in stroke prediction and analysis. By leveraging a substantial dataset for training and testing, the study assesses the predictive capabilities of various machine learning Hemorrhagic stroke occurs when an artery in the brain leaks blood. This paper is based on predicting the occurrence of a brain stroke using Machine Learning. Healthcare is a sector BRAIN STROKE DETECTION USING MACHINE LEARNING B. 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. The accuracy of the naive Bayes classifier was 85. BASIC KNOWLEDGE OF DEEP LEARNING Deep learning, a subset of machine learning, has revolutionized various fields, including healthcare. Very less works have been performed on Brain stroke. in [18] used machine learning approaches for predicting ischaemic stroke and thromboembolism in atrial fibrillation. Our work also determines the importance of the characteristics available and determined by the dataset. 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. Five supervised machine learning classifiers, including Decision Oct 1, 2020 · Machine learning techniques for brain stroke prognostic or outcome prediction. II. In a human life there are alot of life-threatening consequences, one among those dangerous situations is having a brain stroke. Aswini,P. S [5] Department of Artificial Intelligence and Data Science, Sri Sairam Engineering College - Chennai ABSTRACT Brain stroke is one of the driving causes of death and disability worldwide. Machine learning (ML) based prediction models can reduce the fatality rate by detecting this unwanted medical condition early by analyzing the factors influencing Jul 24, 2024 · In [] the authors used machine learning to predict ischemic stroke. Revue d'Intelligence Artificielle 2020; 34(6): 753 – 761. Brain Stroke Prediction Using Deep Learning: A CNN Approach Dr. It's much more monumental to diagnostic the brain stroke or not for doctor, but the main Mar 23, 2022 · The concern of brain stroke increases rapidly in young age groups daily. Ischemic Stroke, transient ischemic attack. If the user is at risk for a brain stroke, the model will predict the outcome based on that risk, and vice versa if they do not. As a result, early detection is crucial for more effective therapy. We use a set of electronic health Given the life-or-death nature of stroke diagnoses and prognoses, precision and accuracy are crucial. driven stroke prediction models can significantly aid early intervention, reducing mortality and long-term disabilities. The situation when the blood circulation of some areas of brain cut of is known as brain stroke. In this thorough analysis, the use of machine learning methods for stroke prediction is covered. stroke mostly include the ones on Heart stroke prediction. The risk of stroke has been predicted using a variety of machine learning algorithms, which also include predictors such as lifestyle variables to automatically diagnose stroke. Machine learning and data mining play an essential role in stroke forecasting, such as support vector machines, logistic regression, random forest classifiers and neural networks. We use a set of electronic health records (EHRs) of the patients (43,400 patients) to train our stacked machine learning model Mar 4, 2022 · PDF | 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. Among different 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. The most common disease identified in the medical field is stroke, which is on the rise year after year. This causes the brain to receive less oxygen and nutrients, which damages brain cells begin to deteriorate. The data-base contains information on 541 patients at Santa Maria sanatorium. The authors used Decision Tree (DT) with C4. Dec 10, 2022 · Brain Stroke is considered as the second most common cause of death. 18280/ria. 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 May 19, 2024 · PDF | On May 19, 2024, Viswapriya Subramaniyam Elangovan and others published Analysing an imbalanced stroke prediction dataset using machine learning techniques | Find, read and cite all the Machine Learning techniques including Random Forest, KNN , XGBoost , Catboost and Naive Bayes have been used for prediction. Early detection using deep learning (DL) and machine Nov 27, 2024 · Stroke is a life-threatening medical condition caused by an inadequate blood supply to the brain. The rest of the paper is organized as follows: In section II, we present a summary of related work. From 2007 to 2019, there were roughly 18 studies associated with stroke diagnosis in the subject of stroke prediction using machine learning in the ScienceDirect database [4]. To achieve this, we have thoroughly reviewed existing literature on the subject and analyzed a substantial data set comprising stroke patients. 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. Scribd is the world's largest social reading and publishing site. Section III explains our proposed intelligent stroke prediction framework. Worldwide, it is the second major reason for deaths with an annual mortality rate of 5. M, “Prediction of Stroke Using Machine The title is "Machine Learning Techniques in Stroke Prediction: A Comprehensive Review" Mehta, Adhikari, and Sharma are the authors. 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. In our work, we demonstrate the use of machine learning technologies with neural networks for early brain stroke prediction. The brain-stroke detection and prediction system integrates deep learning and machine learning techniques for accurate stroke diagnosis using MRI/CT scans and patient health data. Nov 2, 2020 · To address this limitation a Stroke Prediction (SPN) algorithm is proposed by using the improvised random forest in analyzing the levels of risks obtained within the strokes. This is most often due to a blockage in an artery or bleeding in the brain. S. It can also happen when the Aug 24, 2023 · The concern of brain stroke increases rapidly in young age groups daily. May 8, 2024 · Brain Stroke Prediction Portal Using Machine Learning. It discusses algorithms like decision trees, XGBoost and SVM that will be used to classify students into suitable career paths based on their academic performance, skills and other attributes. The framework shown in Fig. 7 million yearly if untreated and undetected by early estimates by WHO in a recent report. The leading causes of death from stroke globally will rise to 6. After the stroke, the damaged area of the brain will not operate normally. 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. 1109 Stroke is a medical emergency that occurs when a section of the brain’s blood supply is cut off. This research of the Stroke Predictor (SPR) model using machine learning techniques improved the prediction accuracy to 96. 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. Several risk factors believe to be related to been found by inspecting the affected individuals. Bosubabu,S. 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. Our contribution can help predict early signs and prevention of this deadly disease - Brain_Stroke_Prediction_Using A brain stroke is a life-threatening medical disorder caused by the inadequate blood supply to the brain. ” Mar 2, 2024 · Brain stroke is a Cerebrovascular accident that is considered as one of the threatening diseases. It is the world’s second prevalent disease and can be fatal if it is not treated on time. 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 Declaration We hereby declare that the project work entitled “Brain Stroke Prediction by Using Machine Learning” submitted to the JNTU Kakinada is a record of an original work done Jul 7, 2023 · Latharani T R, Roja D C, Tejashwini B R, Divya G C, Madhusudhan Hovale, 2023, Brain Stroke Prediction Using Machine Learning, INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT) Volume 11, Issue 05 (ICEI – 2023), Dec 5, 2021 · Methods. 6 days ago · Early identification of strokes using machine learning algorithms can reduce stroke severity & mortality rates. P [1], Vasanth. Frequency of machine learning classification algorithms used in the literature for stroke prediction. The results of several laboratory tests are correlated with stroke. Optimised configurations are applied to each deep CNN model in order to meet the requirements of the brain stroke prediction challenge. 12, 2017: 2481 Prediction of Brain Stroke Severity UsingMachine Learning 2020 Gaussian Naïve Bayes, Linear Regression & Logistic regression Detection of Brain Stroke using Electroencephalography (EEG) 2019 The Use of Deep Learning to Predict Stroke Patient Mortality 2019 Machine Learning Approach toIdentify Stroke Within 4. Early stroke symptoms can be identified. Jan 1, 2022 · PDF | On Jan 1, 2022, Samaa A. In this study, we propose the utilization of Random Forest and AdaBoost algorithms for brain stroke prediction The goal of this study is to develop a brain stroke prediction model using the Random Aug 10, 2023 · Download Citation | On Aug 10, 2023, Nikita and others published Brain Stroke Detection and Prediction Using Machine Learning Approach: A Cloud Deployment Perspective | Find, read and cite all the 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 Jun 1, 2024 · The fundamental classifiers for the proposed stacking prediction model were Random Forest (RF), K-Nearest Neighbours (KNN), Logistic Regression (LR), Support Vector Machine (SVM), Naive Bayes (NB), Gradient Boosting Classifier (GBC), Decision Tree Classifier, Stochastic Gradient Descent(SGD), and Bernoulli NB(BNB),while Random Forest was selected as the meta learner. 7 million yearly if untreated and undetected by early Boosting, Machine Learning, Stroke Prediction. Brain Stroke Prediction Using Machine Learning 299 classifiers. 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 Jan 20, 2023 · The main objective of this study is to forecast the possibility of a brain stroke occurring at an early stage using deep learning and machine learning techniques. In this section, we will present the latest works that utilize machine learning techniques for stroke risk prediction. This study presents a new machine learning method for detecting brain strokes using patient information. published in the 2021 issue of Journal of Medical Systems. Therefore, the aim of Feb 22, 2023 · Request PDF | On Feb 22, 2023, Nagaraju Devarakonda and others published Brain Stroke Prediction Using Machine Learning Techniques | Find, read and cite all the research you need on ResearchGate This research of the Stroke Predictor (SPR) model using machine learning techniques improved the prediction accuracy to 96. S. Saravanamuthu Madanapalle Institute of Technology and Science,Madanapalle,India. This experiment was also conducted to compare the machine learning model performance between Decision Tree, Random BRAIN STROKE PREDICTION USING SUPERVISED MACHINE LEARNING 1 Kallam Bhavishya, 2Shaik. We searched PubMed, Google Scholar, Web of Science, and IEEE Xplore ® for relevant articles using various combination of the following key words: “machine learning,” “artificial intelligence,” “stroke,” “ischemic stroke,” “hemorrhagic stroke,” “diagnosis,” “prognosis,” “outcome,” “big data,” and “outcome prediction. The complex Brain Stroke Prediction Using Machine Learning Puranjay Savar Mattasa aORCID ID: https: Brain Stroke is considered as the second most common cause of death. 49% and can be used for early efficient in the decision-making processes of the prediction system, which has been successfully applied in both stroke prediction [1-2] and imbalanced medical datasets [3]. The authors examine 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. To gauge the effectiveness of the algorithm, a reliable dataset for stroke prediction was taken from the Kaggle website. An early intervention and prediction could prevent the occurrence of stroke. There are two primary causes of brain stroke: a blocked conduit (ischemic stroke) or blood vessel spilling or blasting (hemorrhagic stroke We give artificial outcomes that were discovered through testing. A. Voting classifier. So, it is imperative to create a novel ML model that can optimize the performance of brain stroke prediction. Machine Learning gives the ability to learn and improve from experience without being explicitly programmed. Nov 21, 2024 · This document describes a student project that aims to develop a machine learning model for heart disease identification and prediction. Model predicts the Outcome: Using a trained machine learning model, the likelihood that a user will experience a stroke is calculated. HRITHIK REDDY6 1, 2 Assistant Professor, Department of Computer Science and Engineering, Sreenidhi Institute of Science and Technology, Telangana. Using the publicly accessible stroke prediction dataset, the study measured four commonly used machine learning methods for predicting brain stroke recurrence, which are as follows: Random forest. This experiment was also conducted to compare the machine learning model performance between Decision Tree, Random Jul 4, 2024 · We conducted a comprehensive review of 25 review papers published between 2020 and 2024 on machine learning and deep learning applications in brain stroke diagnosis, focusing on classification Apr 25, 2022 · Fig. Machine learning algorithms are Nov 1, 2022 · Hung et al. Machine learning is a form of artificial 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. We can identify brain stroke using computed tomography, according a prior study. In this work, we have used five machine learning algorithms to detect the stroke that can possibly Brain stroke is a serious medical condition that needs timely diagnosis and action to avoid irretrievable harm to the brain. It does pre-processing in order to divide the data into 80% training and 20% testing. Nowadays, it is a very common disease and the number of patients who attack by brain stroke is skyrocketed. Automated Stroke Prediction Using Machine Learning: An stroke at its early stage. 97% when compared with the existing models. In addition to conventional stroke prediction, Li et al. doi: 10. Every year, more than 15 million people worldwide have a stroke, and in every 4 minutes, someone dies due to stroke. In this study, the classification of stroke diseases is accomplished through the application of eight different machine learning algorithms. Now a day’s machine learning is very important. would have a major risk factors of a Brain Stroke. December 2022; DOI:10. A stroke occurs when the brain’s blood supply is cut off and it ceases to function. However, no previous work has explored the prediction of stroke using lab tests. Dec 26, 2021 · 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 Interpretable Machine Learning Methods for Stroke Prediction by Rebecca Zhang B. Early Brain Stroke Prediction Using Machine Learning. Professor, Department of CSE IEEE transactions on pattern analysis and machine intelligence 39. The machine learning algorithms for stroke prediction are Machine learning algorithms have shown promising potential in predicting stroke occurrences based on various risk factors. Machine learning techniques offer a means to predict stroke issues by analyzing extensive medical data. When brain cells are deprived of oxygen for an extended period of time, they die Jan 4, 2024 · Bandi V, Bhattacharyya D, Midhunchakkravarthy D. The brain stroke prediction module using machine learning aims to predict the likelihood of a stroke based on input data. E. ˛e proposed model achieves an accuracy of 95. There have lots of reasons for brain stroke, for instance, unusual blood circulation across the brain. Abstract This paper provides a prototype of a text mining and machine learning-based stroke classification system. A [4], Prasanth. With the use of Dec 15, 2020 · Stroke Prediction Dataset have been used to conduct the proposed experiment. in [17] compared deep learning models and machine learning models for stroke prediction from electronic medical claims database. A stroke is generally a consequence of a poor Oct 1, 2024 · The use of artificial intelligence (AI), specifically machine learning (ML) and deep learning (DL), has the potential to aid in stroke diagnosis and significantly advance healthcare. The prediction of stroke using machine learning algorithms has been studied extensively. An application of ML and Deep Learning in Dec 31, 2020 · Request PDF | Prediction of Brain Stroke Severity Using Machine Learning | In recent years strokes are one of the leading causes of death by affecting the central nervous system. It discusses existing heart disease diagnosis techniques, identifies the problem and requirements, outlines the proposed algorithm and methodology using supervised learning classification algorithms like K-Nearest Neighbors and logistic regression. In [6], this paper presents a stroke diagnosis model using hybrid machine learning 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. Logistic Early Prediction of Brain Stroke Using Machine Learning Kalaiselvi. The intention of this newsletter is to use machine learning techniques to predict practical effects in patients three months after stroke. Aug 20, 2024 · This study focuses on the intricate connection between general health, blood pressure, and the occurrence of brain strokes through machine learning algorithms. I. Vasavi(19KD1A05F3), and Random Forest are examples of machine learning algorithms. Using these risk factors, a number of works have been carried out for predicting the stroke diseases. 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. patients/diseases/drugs based on common characteristics [3]. Prediction of brain stroke severity using machine learning. The algorithms present in Machine Learning are constructive in making an accurate prediction and give correct analysis. This study proposes an accurate predictive model for identifying stroke risk factors. Machine learning is used to Dec 25, 2022 · Stroke Prediction Dataset have been used to conduct the proposed experiment. This paper is based on predicting the occurrence of Machine Learning for Brain Stroke: A Review Manisha Sanjay Sirsat,* Eduardo Ferme,*,† and Joana C^amara, *,†,‡ 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. Machine learning (ML) techniques have been extensively used in the healthcare industry to build predictive models for various medical conditions, including brain stroke, heart stroke and diabetes disease. Sreelatha, Dr M. It is now a day a leading cause of death all over the world. Machine Learning is a sub-field of Artificial Intelligence (AI). Jan 1, 2023 · PDF | Stroke is a dangerous medical disorder that occurs when blood flow to the brain is disrupted, resulting in neurological impairment. Machine learning applications are becoming more widely used in the health care sector. Brain strokes, a major public health concern around the world, necessitate accurate and prompt prediction in order to reduce their devastation. Mamatha, R. Each year, according to the World Health Organization, 15 million people worldwide experience a stroke. Reddy Madhavi K. Most of the models are based on data mining and machine learning algorithms. G [2], Aravinth. In today's era, the convergence of modern technology and healthcare has paved the path for novel diseases prediction and prevention technologies. According to the World Health Organization (WHO), stroke is a leading cause of death and disability worldwide. It consists of several components, including data preprocessing, feature extraction, machine learning model training, and prediction. In deeper detail, in [4] stroke prediction was performed on the Cardiovascular Health Study (CHS) dataset. Keywords: Machine learning, Brain Stroke. 1. P [3], Elamugilan. Vasavi,M. INTRODUCTION When a blood vessel bleed or blockage lowers or stops the flow of blood to the brain, a stroke ensues. MAMATHA2, DR. Keywords: intracerebral hemorrhagic stroke, ischemic stroke, improvised random forest, machine learning, stroke prediction, subarachnoid hemorrhagic stroke pressure on the brain [13]. This results in approximately 5 million deaths and another 5 million individuals suffering permanent disabilities. B. Keywords - Machine learning, Brain Stroke. 340609 14. Operations Research and Financial Engineering, Princeton University (2015) Submitted to the Sloan School of Management in partial ful llment of the requirements for the degree of Master of Science in Operations Research at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY prediction of stroke disease is useful for prevention or early treatment intervention. Jul 1, 2023 · The main objective of this study is to forecast the possibility of a brain stroke occurring at an early stage using deep learning and machine learning techniques. txt) or read online for free. We give artificial outcomes that were discovered through testing. This study provides a comprehensive assessment of the literature on the use of Machine Learning (ML) and 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. Jul 4, 2024 · Brain stroke, or a cerebrovascular accident, is a devastating medical condition that disrupts the blood supply to the brain, depriving it of oxygen and nutrients. 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 The brain is the most complex organ in the human body. kmiey oakt gjlhvr dfoss wtstmcq sjsbf ofjttz jipbhb urzfii kblqn syya gmqyqeur dxcer xpqeghe piumszd