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Advances in Medical Technologies and Clinical Practice最新文献

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Corona 电晕
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.1515/9780691200026-009
Mansha Sharma, A. Sharma
{"title":"Corona","authors":"Mansha Sharma, A. Sharma","doi":"10.1515/9780691200026-009","DOIUrl":"https://doi.org/10.1515/9780691200026-009","url":null,"abstract":"Coronavirus has come up as the worst nightmare in the form of a pandemic for progressive sapiens in terms of health, wealth, prosperity, and social wellbeing. To date, coronavirus has mutated to seven different shapes evolving into various variants. The main deliberation of catching the disease is carelessness and negligence of the citizens, and in developing countries like India, population and illiteracy makes it even more difficult to control the disease. However, immunity can be the superhero in fighting against the virus that invades the host. Although a strong immunity is important to fight the disease, the symptoms show at a later stage by the body of a human with a stronger immunity and cases are getting critical in this case. After a long struggle, scientists have come up with vaccines that are 90% efficient and show some side effects. The world is expected to function only if ‘herd immunity' is achieved, but it is expected that wearing masks would be the new normal.","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116733093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Investigation of Epileptic Seizures and Sleep Disturbance 癫痫发作与睡眠障碍的调查
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-8018-9.ch004
Bharath V. S., Miraclin F., B. Priyanka, B. K. P., R. M.
{"title":"Investigation of Epileptic Seizures and Sleep Disturbance","authors":"Bharath V. S., Miraclin F., B. Priyanka, B. K. P., R. M.","doi":"10.4018/978-1-7998-8018-9.ch004","DOIUrl":"https://doi.org/10.4018/978-1-7998-8018-9.ch004","url":null,"abstract":"In this chapter, the authors make use of signal processing techniques and machine learning models to analyze the EEG signal. First, the EEG signal is broken down into the frequency sub-bands using a discrete wavelet transform (DWT). Then the kernel principle component analysis (KPCA) method is used to reduce the dimension of data. They input these extracted features into a neural network to find if the patient has an epileptic seizure or not. The results of the classification process due to artificial neural networks (ANN) are studied and analyzed. Also, to recognize the abnormal activities in the EEG signal, caused by changes in neuronal electrochemical activity in epileptic patients, the EEG signal is processed using the Hilbert Huang transform (HHT). Given the wide array of epilepsy, we need to make use of intelligent devices in the treatment of epilepsy by using the patient's neurophysiology for better diagnosis before the clinical operation.","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115741550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Quality Control Applications in the Pharmaceutical and Medical Device Manufacturing Industry 质量控制在制药和医疗器械制造业中的应用
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-9613-5
{"title":"Quality Control Applications in the Pharmaceutical and Medical Device Manufacturing Industry","authors":"","doi":"10.4018/978-1-7998-9613-5","DOIUrl":"https://doi.org/10.4018/978-1-7998-9613-5","url":null,"abstract":"","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126140877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering 神经科学和神经工程中的未来设计和智能计算技术
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-7433-1
{"title":"Futuristic Design and Intelligent Computational Techniques in Neuroscience and Neuroengineering","authors":"","doi":"10.4018/978-1-7998-7433-1","DOIUrl":"https://doi.org/10.4018/978-1-7998-7433-1","url":null,"abstract":"","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129316912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Computational Methods and Algorithms for Medicine and Optimized Clinical Practice 医学和优化临床实践的计算方法和算法
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-8244-1
{"title":"Computational Methods and Algorithms for Medicine and Optimized Clinical Practice","authors":"","doi":"10.4018/978-1-5225-8244-1","DOIUrl":"https://doi.org/10.4018/978-1-5225-8244-1","url":null,"abstract":"","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129779799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Developing an Effective Classification Model for Medical Data Analysis 开发一种有效的医学数据分析分类模型
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-7796-6.CH001
N. A. Mahoto, Abdul Hafeez Babar
{"title":"Developing an Effective Classification Model for Medical Data Analysis","authors":"N. A. Mahoto, Abdul Hafeez Babar","doi":"10.4018/978-1-5225-7796-6.CH001","DOIUrl":"https://doi.org/10.4018/978-1-5225-7796-6.CH001","url":null,"abstract":"The sparse nature of medical data makes knowledge discovery and prediction a complex task for analysis. Machine learning algorithms have produced promising results for diversified data. This chapter constructs the effective classification model for medical data analysis. In particular, nine classification models, namely Naïve Bayes, decision tree (i.e., J48 and Random Forest), multilayer perceptron, radial bias function, k-nearest neighbors, single conjunctive rule learner, support vector machine, and simple logistics have been applied for developing an effective model. Besides, classification models have also been used in conjunction with ensemble learning methods, since ensemble methods significantly increase the predictive outcomes of the classification models. The evaluation of classification models has been measured using accuracy, f-measure, precision, and recall metrics. The empirical results revealed that the combination of ensemble learning methods with classification models produces better predictions in comparison with sole classification model for the medical data.","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130051980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
An Optimized FPGA Architecture for Sleep Level Categorization Using Fuzzed Utilized Machine Learning Approach 基于模糊利用机器学习方法的睡眠水平分类优化FPGA架构
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-8018-9.ch012
B. J., Mariammal Karuthapandian, V. Dhandapani
{"title":"An Optimized FPGA Architecture for Sleep Level Categorization Using Fuzzed Utilized Machine Learning Approach","authors":"B. J., Mariammal Karuthapandian, V. Dhandapani","doi":"10.4018/978-1-7998-8018-9.ch012","DOIUrl":"https://doi.org/10.4018/978-1-7998-8018-9.ch012","url":null,"abstract":"In this chapter, an efficient FPGA architecture is proposed to categorize and analyze the sleep level. This proposed architecture is implemented using four sub parts which are namely preprocessing unit, FIR filtering, self-regulated learning, and fuzzy deduction. The EEG (electro encephalo gram) and EMG (electro myogram) are signal samples are considered for the analysis of this sleep level. The signals are initially preprocessed to remove undesired signal components. Further, a reconfigurable multichannel multiply accumulate (MAC)-based FIR filter is utilized for achieving the desired signal. Then the signal is classified based on the reference data with the use of self-regulated machine learning and fuzzy deduction schemes which involves averaging and thresholding process. Further, the signals are categorized into completely awake level, partially awake level, and sleep level using fuzzy if-then rules. The performance parameters are analyzed in terms of sensitivity, specificity, latency, area occupied, power consumption, and speed enhancement.","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133355534","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Melanoma Image Classification Based on Multivariate Parametric Statistical Tests of Hypothesis 基于多元参数统计假设检验的黑色素瘤图像分类
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-7796-6.CH005
K. Seetharaman
{"title":"Melanoma Image Classification Based on Multivariate Parametric Statistical Tests of Hypothesis","authors":"K. Seetharaman","doi":"10.4018/978-1-5225-7796-6.CH005","DOIUrl":"https://doi.org/10.4018/978-1-5225-7796-6.CH005","url":null,"abstract":"This chapter proposes a novel method, based on the multivariate parametric statistical tests of hypotheses, which classifies the normal skin lesion images and the various stages of the melanoma images. The melanoma images are categorized into two classes, such as initial stage and advanced stage, based on the degree of aggressiveness of the cancer. The region of interest is identified and segmented from the input skin melanoma image. The features, such as HSV color, shape, and texture, are extracted from the region of interest. The features are treated as a feature space, which is assumed to be a multivariate normal random field. The proposed statistical tests are employed to identify and classify the melanoma images. The proposed method yields an average correct classification up to 91.55% for the normal skin lesion versus the initial and the advanced stages of the melanoma images, up to 91.39% for initial stage melanoma versus the normal skin lesion and the advanced stages melanoma, and up to 92.27% for the advanced stage melanoma versus the normal skin lesion and the initial stage melanoma. The proposed method yields better results.","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129207004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Medical Image Segmentation and Analysis 医学图像分割与分析
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-5225-7796-6.CH007
R. Kashyap
{"title":"Medical Image Segmentation and Analysis","authors":"R. Kashyap","doi":"10.4018/978-1-5225-7796-6.CH007","DOIUrl":"https://doi.org/10.4018/978-1-5225-7796-6.CH007","url":null,"abstract":"An improved energy-based technique with a Lattice Boltzmann method organizes with the neighborhood and global energy terms, local term propels to pull the frame and constrain it to protest limit, decides noteworthy points of interest not confined to, snappy planning, automation, invariance of exact medical image segmentation, and analysis. Consequently, the worldwide vitality fitting term drives the advancement of the frame at a division of the question limit. The worldwide vitality term relies upon the worldwide division computation, which can better catch drive information of pictures than mixture area-based dynamic shape technique. Both neighborhood and worldwide terms are ordinarily acclimatized to construct a level set strategy to divide pictures with exactness. The level set technique with Boltzmann system uses neighborhood mean, a quality which engages it as far as possible. The proposed chapter gathers gainful purposes of intrigue not stuck just using expedient process, computerization, and right helpful picture partitions.","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128544888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Smart Driver Monitoring System Using AI 使用AI的智能驾驶员监控系统
Advances in Medical Technologies and Clinical Practice Pub Date : 1900-01-01 DOI: 10.4018/978-1-7998-8018-9.ch013
Shubhi Shaily, Srikaran Krishnan, Saisriram Natarajan, P. Sasikumar
{"title":"Smart Driver Monitoring System Using AI","authors":"Shubhi Shaily, Srikaran Krishnan, Saisriram Natarajan, P. Sasikumar","doi":"10.4018/978-1-7998-8018-9.ch013","DOIUrl":"https://doi.org/10.4018/978-1-7998-8018-9.ch013","url":null,"abstract":"This chapter provides a contemporary solution to driver drowsiness and fatigue detection on-board whilst the driver is driving the car. The mechanism provided is both non-intrusive relatively and involves the use of artificial intelligence networks. This would aid in providing accurate and desired results thereby avoiding damage generally caused due to negligence and imposters in vulnerable industries that involve massive manpower and inventory. The system created will work based on vehicle details received from the OBD-II and the camera mounted on the dashboard to monitor the driver. As the driver enters the car, he initiates the authentication process when he turns the ignition knob or presses the start stop button in an attempt to start the car, and the on-board camera is turned on. Such efficient management could save the responsible company damages caused and the subsequent dent in their capital.","PeriodicalId":225442,"journal":{"name":"Advances in Medical Technologies and Clinical Practice","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114144720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
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