Search Results - (( java implication based algorithm ) OR ( diabetes classification problems algorithm ))

Hybridization Of Optimized Support Vector Machine And Artificial Neural Network For The Diabetic Retinopathy Classification Problem by Kader, Nur Izzati Ab

“…Due to the success of many classification problems been proposed with good result, k-Nearest Neighbour, Artificial Neural Network, and Support Vector Machine algorithms are used in this research.…”
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Classification of diabetic retinopathy clinical features using image enhancement technique and convolutional neural network / Abdul Hafiz Abu Samah by Abu Samah, Abdul Hafiz

“…In general, this thesis introduces an automated machine learning algorithm for detecting diabetic retinopathy (DR) in fundus images. …”
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Machine Learning Algorithms for Diabetes Prediction: A Review Paper by Al-Sideiri A., Cob Z.B.C., Drus S.B.M.

Multi-label risk diabetes complication prediction model using deep neural network with multi-channel weighted dropout by Dzakiyullah, Nur Rachman

“…The first experiment revealed that the Algorithm Adaptation framework outperformed Problem Transformation methods across most metrics. …”
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An Improved Diabetes Risk Prediction Framework : An Indonesian Case Study by Sutanto, Daniel Hartono

“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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An improved data classification framework based on fractional particle swarm optimization by Sherwani, Fahad

“…It can be concluded from the simulation results that the proposed MOFPSO-ERNN classification algorithm demonstrated good classification performance in terms of classification accuracy (Breast Cancer = 99.01%, EEG = 99.99%, PIMA Indian Diabetes = 99.37%, Iris = 99.6%, Thyroid = 99.88%) as compared to the existing hybrid classification techniques. …”
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MEDCnet : A Memory Efficient Approach for Processing High-Resolution Fundus Images for Diabetic Retinopathy Classification Using CNN by Mohsin, Butt, Dayang Nurfatimah, Awang Iskandar, Majid, Ali Khan, Ghazanfar, Latif, Abul, Bashar

“…These detailed features are then utilized for classification based on standard machine learning algorithms. …”
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Neuro fuzzy classification and detection technique for bioinformatics problems by Othman, Mohd. Fauzi, Moh, Thomas Shan Yau

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Enhancement of new smooth support vector machines for classification problems by Santi Wulan, Purnami

“…Research on Smooth Support Vector Machine (SSVM) for classification problem is an active field in data mining. …”
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Development of Deep Learning Classification Model for Diabetic Retinopathy Detection and Grading by Nurul Mirza Afiqah, Tajudin

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Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm by Rehman Gillani, Syed Muhammad Zubair

“…The performance of the proposed method known as ‘Gradient Descent Method with Adaptive Momentum (GDAM)’ is compared with ‘Gradient Descent Method with Adaptive Gain (GDM-AG)’ (Nazri, 2007) and ‘Gradient Descent with Simple Momentum (GDM)’ by performing simulations on classification problems. The results show that GDAM is a better approach than previous methods with an accuracy ratio of 1.0 for classification problems like ix Thyroid disease, Heart disease, Breast Cancer, Pima Indian Diabetes, Wine Quality, Australian Credit-card approval problem and Mushroom problem. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome by Salari, Nader

“…The model could also be utilized for classification tasks in the other medical fields such as breast cancer and diabetes. …”
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Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

“…According to World Health Organization (WHO), the percentage of health problems occurring in the world population, such as diabetes, heart problem, and high blood pressure rapidly increases from year-to-year. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush