Search Results - (( developing care learning algorithm ) OR ( java implication based algorithm ))

Diabetes Diagnosis And Level Of Care Fuzzy Rule-Based Model Utilizing Supervised Machine Learning For Classification And Prediction by Mohd Aris, Teh Noranis, Abu Bakar, Azuraliza, Mahiddin, Normadiah, Zolkepli, Maslina

“…Overall, the proposed fuzzy rule-based diabetes diagnosis and level of care fuzzy model works well with most of the machine learning algorithms tested. …”
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Prediction of Fetal Health Status Using Machine Learning by Naidile S, Saragodu, Shreedhara N, Hegde, Harprith, Kaur

“…The results of this study demonstrate how machine learning algorithms can accurately forecast fetal health status. …”
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Mortality prediction in critically ill patients using machine learning score by Dzaharudin, Fatimah, Md Ralib, Azrina, Jamaludin, Ummu Kulthum, Mat Nor, Mohd Basri, Tumian, Afidalina, Har, Lim Chiew, Ceng, T C

“…The aim of this study is to develop a machine learning (ML) based algorithm to improve the prediction of patient mortality for Malaysian ICU and evaluate the algorithm to determine whether it improves mortality prediction relative to the Simplified Acute Physiology Score (SAPS II) and Sequential Organ Failure Assessment Score (SOFA) scores. …”
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Machine learning-based risk prediction model for medication administration errors in neonatal intensive care units: a prospective direct observational study by Henry Basil, Josephine, Lim, Wern Han, Syed Ahmad, Sharifah M., Menon Premakumar, Chandini, Mohd Tahir, Nurul Ain, Mhd Ali, Adliah, Seman, Zamtira, Ishak, Shareena, Mohamed Shah, Noraida

“…Each observation was independently assessed for errors. Ten machine learning (ML) algorithms were applied with features derived from systematic reviews, incident reports, and expert consensus. …”
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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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Polymorphic malware detection based on dynamic analysis and supervised machine learning / Nur Syuhada Selamat by Selamat, Nur Syuhada

“…The benefit of this work indicated that the implementation of a feature selection technique plays an important role in machine learning algorithms to increase the performance of detection.…”
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The influence of machine learning on the predictive performance of cross-project defect prediction: empirical analysis by Bala, Yahaya Zakariyau, Samat, Pathiah Abdul, Sharif, Khaironi Yatim, Manshor, Noridayu

“…This empirical investigation delves into the influence of machine learning (ML) algorithms in the realm of cross-project defect prediction, employing the AEEEEM dataset as a foundation. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

“…Support Vector Machine (SVM) is among the popular learning algorithm for classification in soft computing techniques. …”
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Predictive Modelling of Stroke Occurrence among Patients using Machine Learning by Sures, Narayasamy, Thilagamalar, Maniam

“…The model exhibited excellent sensitivity and specificity, enabling effective stratification of patients based on their stroke likelihood. Developing an accurate stroke prediction model using machine learning holds immense potential for proactive healthcare strategies and personalized patient care. …”
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A framework for the development of an optimized artificial intelligence model for diabetes mellitus prediction and treatment recommendation by Islam, Md Ziarul, Hassan, Mohd Khairul Azmi, Amir Hussin, Amir 'Aatieff

“…Combining machine learning, deep learning algorithms, and ensemble techniques like model stacking, the framework aims to achieve high prediction accuracy, balancing sensitivity and specificity, to support clinical decision-making. …”
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NLP- based for providing mental health support in mobile application / Muhammad Amirul Roslan by Roslan, Muhammad Amirul

“…The project demonstrates the effectiveness of combining NLP and mobile technology through careful design and implementation. Future enhancements, such as advanced machine learning algorithms and user interface improvements, are proposed to further enhance functionality. …”
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Hybrid bayesian network in neural network based deep learning framework for detection of obstructive sleep apnea syndrome by Farouk, F.N.B.M., Anwar, T., Zakaria, N.B.

“…The results of this research will produce a useful and beneficial clinical workflow for future support in health care. The model will be developed based on the methods of analysis and the quantitative data used to compromise the developing of Hybrid Bayesian Network in Neural Network using Deep Learning Algorithm. …”
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Optimizing high-density aquaculture rotifer Detection using deep learning algorithm by Alixson Polumpung, Kit Guan Lim, Min Keng Tan, Sitti Raehanah Muhamad Shaleh, Renee Ka Yin Chin, Kenneth Teo Tze Kin

“…First, dataset acquisition from digital microscope and manual labelling annotation divided by 60, 20 and 20 percent for training, validation and testing consecutively. Second, is to develop the deep learning algorithm based on YOLOv3. …”
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Using machine learning algorithms to develop a clinical 2 decision-making tool for COVID-19 inpatients by Vepa, Abhinav, Saleem, Amer, Rakhshan, Kambiz, Daneshkhah, Alireza

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Mortality prediction in critically ill patients using machine learning score by Fatimah, Dzaharudin, Azrina, Md Ralib, Ummu Kulthum, Jamaludin, Mohd Basri, Mat Nor, Afidalina, Tumian, Har, Lim Chiew, Ceng, T. C.

“…The aim of this study is to develop a machine learning (ML) based algorithm to improve the prediction of patient mortality for Malaysian ICU and evaluate the algorithm to determine whether it improves mortality prediction relative to the Simplified Acute Physiology Score (SAPS II) and Sequential Organ Failure Assessment Score (SOFA) scores. …”
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Innovative smart phone learning system for graphical systems within covid-19 pandemic by Tawafak R.M., Alfarsi G., Jabbar J.

“…This paper used the Technology Acceptance Model (TAM) as an m-learning model, and Bresenham�s line algorithm is a calculation system implemented by applications. …”

Utilizing machine learning technique for emotion learning and aiding mental health issues by Husin, Nor Azura, Wan, Gibson Liang, Kamaruzaman, Nurul Nadhrah

“…EMOICE will use human speech to extract features such as pitch, voice quality, and voice spectral, which will be used by the algorithm to learn and produce accurate results. EMOICE will employ machine learning techniques, and among the classifiers tested and compared, 1D-Convolutional Neural Network (1D-CNN) has a high accuracy value of 94.78 percent. …”
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A systematic literature review on the application of artificial intelligence in enhancing care for kidney diseases patients by Rahman, Md Saidur, Md Nor, Nor Saadah

“…The objective of the research is to systematically evaluate AI technology in CKD from a patient-centered perspective of care improvement for patients with CKD. Fourteen studies published from 2018 to 2024 were reviewed in the systematic review to learn how AI technology was incorporated to improve care for CKD patients. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Exploring the ethical dimensions of artificial intelligence and robotics in dental education by Sim, Galvin Siang Lin, Foo, Jia Yee, Goh, Shu Meng, Alam, Mohammad Khursheed

“…Their integration in dental education offers opportunities to enhance learning, diagnostics, treatment planning, and patient care. …”
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