International Journal of Cancer Management
The Official Journal of Cancer Research Center (CRC), Shahid Beheshti University of Medical Sciences
Scopus by Title (Ref)
2. Application of survival analysis in veterinary practice – The relationship between PTBC infection and culling in dairy cattle herds
- Katalin V. , et al.
3. Cox-Sage: enhancing Cox proportional hazards model with interpretable graph neural networks for cancer prognosis
- Mao R. , et al.
4. Prognostic Factors Associated with Breast Cancer-Specific Survival from 1995 to 2022: A Systematic Review and Meta-Analysis of 1,386,663 Cases from 30 Countries
- Abdul Rahman H. , et al.
5. Comparing the performance of statistical, machine learning, and deep learning algorithms to predict time-to-event: A simulation study for conversion to mild cognitive impairment
- Billichová M. , et al.
7. Comparative impact of the affordable care act on breast cancer outcomes among women in two US states
- Akinyemi O. , et al.
8. Statistical Models in Cancer Management
- Chandramohan S. , et al.
9. Early prediction of response to palliative chemotherapy in patients with stage-IV gastric and esophageal cancer
- Ma X. , et al.
10. Chronological horse herd optimization-based gene selection with deep learning towards survival prediction using PAN-Cancer gene-expression data
- Majji R. , et al.
11. Survival analysis
- Vierra A. , et al.
12. Factors Associated with Recurrence of Breast Cancer Using Cox Proportional Hazard Model
- Ashleik N. , et al.
13. Sphingolipids: A roadmap from biomarker identification to clinical application
- Bhadwal P. , et al.
14. Kidney Graft Failure and Patient Survival Modelling Based on Competing Risks Under Nonproportional Hazards
- Valenta Z. , et al.
16. Deep learning algorithm reveals probabilities of stage-specific time to conversion in individuals with neurodegenerative disease LATE
- Wu X. , et al.
17. Prediction and interpretation of cancer survival using graph convolution neural networks
- Ramirez R. , et al.
18. Fenchel duality of Cox partial likelihood with an application in survival kernel learning
- Wilson C.M. , et al.
19. Time-to-event prediction using survival analysis methods for Alzheimer's disease progression
- Sharma R. , et al.
20. Applications of personalised signalling network models in precision oncology
- Hastings J.F. , et al.
21. Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data
- Hao J. , et al.
22. Random Forest Modeling for Survival Analysis of Cancer Recurrences
- Imani F. , et al.
23. Survival analysis of breast cancer patients with different treatments: A multicentric clinicopathological study
- Malik S.S. , et al.
25. Applying Cox Regression in Time to Event Data
- Abdelsalam N.O. , et al.