Browsing by Author "Mohamad Nasarudin Adnan"
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Publication Graphical Plot and Correlation Analysis for Establishing an Acceptance of Future Intention of Exclusive Breastfeeding among Medical and Dental Students A Study from Hospital Universiti Sains Malaysia(Journal of Coastal Life Medicine, 2023) ;Noraini Mohamad ;Wan Muhamad Amir W Ahmad ;Mohamad Shafiq Mohd Ibrahim ;Nor Azlida Aleng ;Nurfadhlina Abdul Halim ;Mohamad Nasarudin AdnanFarah Muna Mohamad GhazaliThe objective of this research was to identify and analyse the correlation between various factors that could impact the likelihood of medical and dental students at Hospital Universiti Sains Malaysia (Hospital USM), Kelantan, Malaysia to intend to exclusively breastfeed in the future. The questionnaire was designed and validated. The validated questionnaire was distributed among medical dan dental students. The study involved 162 participants, comprising 25 (15.4%) students from the dental program and 137 (84.6%) from the medical program. There are 56 (34.6%) male and 106 (65.4%) female involved in this study. At first, the collected data were analysed using MINITAB software through the contour plot and surface plot. Second, the data were analysed using the Spearman correlation. The result from correlation analysis shows that, most of the studied factors related to general knowledge rather than other studied factors. The discovery indicates that one approach to promoting the acceptance of exclusive breastfeeding among medical and dental students is by improving their general knowledge about the topic. The correlation analysis, 3-D plot, and contour plot demonstrate that factors such as gender, marital status, and specific and general knowledge are associated with the intention to exclusively breastfeed in the future. This finding is very important especially for awareness education, and establishing the future exclusive breastfeeding practiced among future parents. - Some of the metrics are blocked by yourconsent settings
Publication Maxillofacial Fracture Trauma: Orbital Walls Fracture And Their Association Using Multilayer Neural Network Perspectives(publishoa, 2022) ;Wan Muhamad Amir W Ahmad ;Ramizu Shaari ;Nor Farid Mohd Noor ;Mohamad Nasarudin Adnan ;Nurul Asyikin Nizam Akbar ;Nor Azlida Aleng ;Farah Muna Mohamad Ghazali ;Nurfadhlina Abdul Halim ;Mohamad Shafiq Mohd Ibrahim ;Nurul Husna MustapaMuhammad Azeem YaqoobObjective: This study aims to find the association of fractured orbital walls with other possible fractures reported in the maxillofacial trauma cases in the Oral Maxillofacial Clinic Oral Maxillofacial ward, Hospital USM Kelantan, Malaysia. Materials and methods: From 2013 to June 2018, records of patients who sustained maxillofacial fractures and presented them to the Accident and Emergency Department, Oral Maxillofacial Clinic, Hospital USM were reviewed, recorded, and analyzed. Data were obtained from 294 patients who met the study's eligibility requirements. The medical records of every patient with a comprehensive medical history were reviewed. The following factors were studied: age, gender, zygomatic arch, maxillary sinus, orbital wall, symphysis of the mandible, parasymphysis, and the condyle. The broken orbital walls in these patients were examined in detail. In the first stage, all of the variables that have been picked will be assessed for their significance from a clinical standpoint. All potential factors contributing to the orbital wall fracture were analyzed using the SPSS and R studio programs. As a result of meeting the inclusion criteria, 294 patients' data has been gathered. Each patient who had a complete medical record was subjected to an examination. In these patients, the cracked orbital walls were examined in greater depth. All chosen variables will be tested in the first stage to see if they are clinically significant. Results: The participants in this study were 228 men (77.6%) and 66 women (22.4%). It was found that the most common age ranges are 11-20 years (39.8%), 21-30 years, and 31-40 years (26.2%). According to Spearman correlation, all of the studied variables have a significant accosiation, with a p-value of less than 0.05. According to the findings of the multiple logistic regression, it was discovered that gender is significant, [0.2652 (0.1761); p < 0.25], Zygomatic Arch fracture, [ (SE)= -0.4511(0.2403); p < 0.25], Maxillary Sinus, [ (SE)= -0.5917 (0.2403) ; p < 0.25], Symphysis of the mandible, [ (SE)= 2.4826 (0.7298); p < 0.05], the condyle of the mandible, [ (SE) = 0.9479 (0.4315); exp (0.9479) = 2.58 3 times], the body of the mandible, [ (SE)= 0.4893 (0.4315) ; p < 0.25] and the angle of the mandible, [ (SE) = 0.6911 (0.4286); p < 0.25]. The validation of the factor through the Multilayer Neural Network (MLNN) and the accuracy obtained 97.71% with the predicted mean square error (PMSE) 0.159%. Conclusion: The matrix spearman correlation, multiple logistic regression, and neural network uncovered a clear association between orbital wall fracture and several other parameters. This discovery will help researchers understand the most common orbital wall fracture causes in maxillofacial trauma. - Some of the metrics are blocked by yourconsent settings
Publication Modeling Cholesterol Levels in Patients with Dyslipidemia and Type 2 Diabetes Mellitus Using an Integrated Statistical Method(Business School, Instituto Tecnologico de Costa Rica, 2023) ;Wan Muhamad Amir W Ahmad ;Nor Azlida Aleng ;Nurfadhlina Abdul Halim ;Nor Farid Mohd Noor ;Mohamad Shafiq Mohd Ibrahim ;Nur Fatiha Ghazalli ;Mohamad Nasarudin AdnanFarah Muna Mohamad GhazaliBackground: Cholesterol levels in the blood, comprising both LDL and HDL cholesterol, can lead to artery plaque formation and potential blockages. Researchers are studying cholesterol levels in individuals with dyslipidemia and type 2 diabetes mellitus. Objective: The objective of this paper is to utilize the developed methodology to model the factor associated with the total cholesterol status in patients with dyslipidemia and type 2 diabetes mellitus. This undertaking has the potential to improve the prediction of total cholesterol levels among the analyzed patients by integrating comprehensive supplementary data from a statistical standpoint. Material and Methods: The data was collected from Hospital Universiti Sains Malaysia (Hospital USM), using statistical modelling techniques to evaluate data descriptions of numerous variables, including height, total cholesterol, triglyceride levels, low-density lipoprotein (LDL) levels, high-density lipoprotein (HDL) levels, and alkaline phosphatase (ALP) levels. The developed method was implemented and evaluated using the R-Studio, employing a neural network model with bootstrapping method and response surface methodology. Results: Our proposed method showed superior accuracy when dividing data into training and testing sets, offering a more precise prediction. The neural network's mean square error was approximately 0.021, demonstrating high precision. Conclusion: In this study, the proposed model demonstrates the method's capability for the improvement of research methodology. The outcome suggests that the methodology established for this investigation is capable of producing favourable results. The study's final analysis demonstrates that the model technique created for research is preferable.