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Research ArticleOpen accessIn the abstractDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,346 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Invariant Translation to Denoise Electroencephalogram SignalsJanett Walters-Williams, Yan LiProblem statement: Because of the distance between the skull and the brain and their different resistivity's, Electroencephalogram (EEG) recordings on a machine is usually mixed with the activities generated within the area called noise. EEG signals have been used to diagnose major brain diseases such as Epilepsy, narcolepsy and dementia. The presence of these noises however can result in misdiagnosis, … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 5 Oct 2011 · 7,515 accessesView PDFCite
Research ArticleOpen accessIn the abstractFault Detection and Classification in Power Electronic Circuits Using Wavelet Transform and Neural NetworkVenugopal Prasannamoorthy, Nanjundappan DevarajanProblem statement: The identification of faults in any analog circuit is highly required to ensure the reliability of the circuit. Early detection of faults in a circuit can greatly assist in maintenance of the system by avoiding possibly harmful damage borne out of the fault. Approach: A novel method for establishing a fault dictionary using Wavelet transform is presented. The … …Journal of Computer Science, Vol. 7, Issue 1 · 15 Jan 2011 · 8,419 accessesView PDFCite
Research ArticleOpen accessIn the abstractSwarm Negative Selection Algorithm for Electroencephalogram Signals ClassificationNasser Omer Sahel Ba-Karait, Siti Mariyam Shamsuddin, Rubita SudirmanProblem statement: The process of epilepsy diagnosis from EEG signals by a human scorer is a very time consuming and costly task considering the large number of epileptic patients admitted to the hospitals and the large amount of data needs to be scored. Therefore, there is a strong need to automate this process. Such automated systems must rely on robust … …Journal of Computer Science, Vol. 5, Issue 12 · 31 Dec 2009 · 7,209 accessesView PDFCite
Research ArticleOpen accessIn the abstractHepatitis B Diagnosis Using Logical Inference and Self-Organizing MapGhumbre Shashikant Uttreshwar, A.A. GhatolDespite all the standardization efforts made, medical diagnosis is still regarded as an art owing to the fact that that medical diagnosis requires an expertise in handling the uncertainty which is unavailable in today's computing machinery. Though artificial intelligence is not a new concept it has been widely recognized as a new technology in computer science. Numerous areas such as … …Journal of Computer Science, Vol. 4, Issue 12 · 31 Dec 2008 · 6,878 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Time Series Forecasting for the Cumulative Confirmed and Critical Cases of the Covid-19 Pandemic in Saudi Arabia using Autoregressive Integrated Moving Average (ARIMA) ModelSamer H. Atawneh, Osamah A.M. Ghaleb, Ahmad MohdAziz Hussein et al.Reviews at present, different machine learning techniques and algorithms have been applied for predicting significant factors of the Coronavirus Disease-2019 (COVID-19) such as the outbreak and diagnosis. In this study, the most accurate time series forecasting model, namely, the Autoregressive Integrated Moving Average (ARIMA) model is used to forecast the expected cumulative number of confirmed and critical cases in Saudi … …Journal of Computer Science, Vol. 16, Issue 9 · 30 Sep 2020 · 7,602 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Analysis of Heart Disease for Diabetic Patients Using Recursive Feature Elimination with Random ForestBindushree Doddasiddavanahalli Channabasavaraju, Udayarani VinayakamurthyData Mining Techniques are used in many areas like banking, healthcare, education because of extracting relevant information from the database. Many algorithms in data mining are used to predict the disease to reduce the patient treatment cost as well as increase the diagnosis accuracy. In this research work, the risk level of diabetic heart disease patient can be predicted using … …Journal of Computer Science, Vol. 16, Issue 1 · 27 Jan 2020 · 7,936 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplications of Machine Learning in Building Energy Prediction and SavingsPriyan Rai, Dr. Nabil Nassif, Kevin Eaton, Alexander RodriguesIn a constantly advancing world with growing needs, buildings play in important role in the daily functioning of the society. Developing more and more advanced techniques to optimize the working of these buildings is highly important for a constant growth. Modern computational techniques have opened doors to create advanced models that can utilize efficient techniques to produce highly accurate results. … …Energy Research Journal, Vol. 10, Issue 1 · 15 Mar 2019 · 8,041 accessesView PDFCite
Review ArticleOpen accessIn the abstractVisualization of Data Mining Techniques for the Prediction of Breast Cancer with High Accuracy RatesVasudev Sharma, Raj Kumar Rajasekaran, Shreya BadhrinarayananBreast cancer is one of the leading causes of death in women worldwide. Around one in 30 women are affected by breast cancer. Mammography has helped in detecting breast cancer in the early stages which have reduced mortality. The diagnosis of breast cancer is dependent on a variety of parameters. In this paper, we aim to create the best model … …Journal of Computer Science, Vol. 15, Issue 1 · 21 Jan 2019 · 8,955 accessesView PDFCite
Review ArticleOpen accessIn the abstractHealthcare Driven by Big Data AnalyticsCheryl Ann Alexander, Lidong WangText messages and social network posts are often included in big data and are frequently invaluable sources of health data. When machine learning or data mining is used, it is important to perform an automatic process for integrating all available and related health data. Artificial Neural Network (ANN) is one of the machine learning methods flexible in using algorithms to … …American Journal of Engineering and Applied Sciences, Vol. 11, Issue 3 · 28 Sep 2018 · 7,403 accessesView PDFCite