| 1 | Heart Disease Diagnosis Using the Brute Force Algorithm and Machine Learning Techniques显示文摘Heart disease is one of the leading causes of death in the world today.Prediction of heart disease is a prominent topic in the clinical data processing.To increase patient survival rates,early diagnosis of heart disease is an important field of research in the medical field.There are many studies on the prediction of heart disease,but limited work is done on the selection of features.The selection of features is one of the best techniques for the diagnosis of heart diseases.In this research paper,we find optimal features using the brute-force algorithm,and machine learning techniques are used to improve the accuracy of heart disease prediction.For performance evaluation,accuracy,sensitivity,and specificity are used with split and cross-validation techniques.The results of the proposed technique are evaluated in three different heart disease datasets with a different number of records,and the proposed technique is found to have superior performance.The selection of optimized features generated by the brute force algorithm is used as input to machine learning algorithms such as Support Vector Machine(SVM),Random Forest(RF),K Nearest Neighbor(KNN),and Naive Bayes(NB).The proposed technique achieved 97%accuracy with Naive Bayes through split validation and 95%accuracy with Random Forest through cross-validation.Naive Bayes and Random Forest are found to outperform other classification approaches when accurately evaluated.The results of the proposed technique are compared with the results of the existing study,and the results of the proposed technique are found to be better than other state-of-the-artmethods.Therefore,our proposed approach plays an important role in the selection of important features and the automatic detection of heart disease. | Junaid Rashid Samina Kanwal Jungeun Kim Muhammad Wasif Nisar Usman Naseem Amir Hussain | 2022 | Computers, Materials & Continua2022，，8： | 0 |
| 2 | Metal-Doped Brushite Cement for Bone Regeneration显示文摘For the past several years,calcium phosphate cement was used in the biomedical applications.Outstanding biocompatibility,good bioactivity,self-setting qualities,minimum setting degree,appropriate toughness,and simple shape to accommodate any difficult geometry are among their most notable attributes.Calcium phosphate has some types and brushite is one of the most attractive mineral for bone repair application.Brushite is extensively employed in filling fractures and trauma treatments as a bone substituted material.This kind of material can potentially be used as a medicine delivery device.The replacement of metal,such as magnesium,zinc,and strontium ions,into the calcium phosphate structure is a major research topic these days.Brushite cement has low mechanical strength and quick setting rate.It is possible to produce biomaterials with higher mechanical characteristics.By adding metal that are great potential in controlling cellular density when included into biomaterials.As a result,it is a successful method to develop quite well regenerative medicine.This paper provides a detailed summary of the present achievements of metal-doped brushite cement for bone repair and healing process.The major purpose of this work is to give a simple but thorough analysis of current successes in brushite cement doped with Zn,Mg,Sr,and other ions as well as to highlight new advancements and prospects.The impact of metal replacement on cement physical and chemical properties,including microstructure,setting time,injectability,mechanical property,and ion release,is explored.The metal-doped cement has osteogenesis,angiogenesis,and antibacterial properties,as well as their prospective utility as drug carriers,also considered. | Muhammad Aqib Aneela Anwar Humayun Ajaz Samina Akbar Ahsan Manzoor Maham Abid Zohaib Waheed Qudsia Kanwal | 2023 | Journal of Bionic Engineering2023，20，6： | 0 |
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