Biostatistical Processes in Gastrointestinal Cancers: Better Data, Better Decisions
Diagnosis and Treatment of Gastrointestinal Cancers, NOVA Publications , ss.411-419, 2025
- Yayın Türü: Kitapta Bölüm / Araştırma Kitabı
- Basım Tarihi: 2025
- Yayınevi: NOVA Publications
- Sayfa Sayıları: ss.411-419
- Anahtar Kelimeler: biostatistical process, gastrointestinal cancers, risk factors
- Karadeniz Teknik Üniversitesi Adresli: Evet
Özet
Gastrointestinal cancers account for approximately one-quarter of all cancer cases and onethird of cancer-related deaths globally. This emphasizes the importance of biostatistical methods and evidence-based medical practices in the early diagnosis, prognosis, and treatment of these diseases. In terms of the accuracy and reliability of the study, the research should begin by calculating the sufficient sample size from the very beginning. In gastrointestinal cancer studies, data are usually collected from various sources, such as electronic health records, biopsies, and genomic and proteomic data. The accuracy and reliability of these data ensure that the study results are reliable. The management of missing data is also important; incorrect or missing data can negatively affect the analysis results. The statistical analysis techniques employed in these studies include logistic regression, Kaplan-Meier survival analysis, the Cox proportional hazards model, and machine learning algorithms. In particular, models developed using machine learning offer significant advancements in areas such as early diagnosis, staging, and prognostic prediction. In reporting study outcomes, it is essential to emphasize both the clinical and statistical significance of the results, clearly define the study's limitations, and propose directions for future research. Finally, the bibliometric analysis shows that the prominent topics in the biostatistical processes of gastrointestinal cancer research in recent years are machine learning and artificial intelligence technologies.