Dr. Nurliyana Binti Juhan
Dr. Nurliyana Binti Juhan
Pusat Persediaan Sains Dan Teknologi · Pusat Persediaan Sains Dan Teknologi, UMS
liyana87@ums.edu.my
Summary

My research expertise is anchored in the fields of Medical Statistics, Data Analysis, and Bayesian Modelling, where I have dedicated my efforts to advancing statistical methodologies in the context of medical research. With a keen focus on extracting meaningful insights from complex healthcare datasets, my work contributes to evidence-based decision-making and enhances the overall landscape of medical inquiry. Beyond the realm of Medical Statistics, my research portfolio extends into diverse areas, including Mathematics Education and Machine Learning. This multidisciplinary engagement underscores my commitment to exploring innovative intersections and applying statistical techniques across various domains, fostering a comprehensive and adaptable approach to research.

Dr. Nurliyana Binti Juhan holds DOKTOR FALSAFAH (MATEMATIK) from Universiti Teknologi Malaysia (Skudai) , among other qualifications, and has established themselves as a respected expert in their field.

Education
Doktor Falsafah (matematik)
Ijazah Sarjana Sains (statistik)
Ijazah Sarjana Muda Pendidikan Dengan Kepujian (pendidikan Dengan Sains)
Stats
Publications:
50
Projects:
6
Grants:
RM 436,000.00
Scopus Metrics
Scopus Author ID:
55913868100
H-Index:
3
Documents:
18
Citations:
30
Research Interests
BIOINFORMATICS - Epidemiological and Disease Modelling
EDUCATION - STEM Education
INFORMATION AND COMMUNICATION TECHNOLOGY (ICT) - Predictive Analytics in Machine Learning
SPECIALIST TOPICS IN MATHEMATICS - Mathematics and Statistics for Science and Engineering
STATISTICAL STUDIES - Bayesian Statistics
STATISTICAL STUDIES - Biostatistics and Medical Statistics
STATISTICAL STUDIES - Exploratory Data Analysis (Including Statistical Modelling)
Latest Grants
Comparison Of Supervised Learning Algorithms In Identifying Influential Factors In Students’ Mathematics Performance.
Statistical Modelling Of Disease Prognosis Based On Complete Blood Count Data
Bayesian Approach To Support Triaging Of Renal Disease And Diabetes Patients Using Complete Blood Count Test Data
Latest Publications
Application Of Exploratory And Confirmatory Factor Analysis To Model Loneliness Dimensions Among Pre-university Students
Performance Analysis Of Simulation-based Laboratory Teaching On Topics Related To Polymerase Chain Reaction Among Pre-university Students
Investigating The Relationship Between Mental Health And Physical Activity: Insights From Phq-9 And Ipaq Data
Chapter 11 Future Prospects And Conclusion
Modelling Malaysian Mortality Improvement Using A Hybrid Logistic Spline
Previous Appointments
Administrative Positions