Survival Prediction from Imbalance colorectal cancer dataset using hybrid sampling methods and tree-based classifiers

Background and Objective: Colorectal cancer is a high mortality cancer. Clinical data analysis plays a crucial role in predicting the survival of colorectal cancer patients, enabling clinicians to make informed treatment decisions. However, utilizing clinical data can be challenging, especially when dealing with imbalanced outcomes. This paper focuses on developing algorithms to predict 1-, 3-, and 5-year survival of colorectal cancer patients using clinical datasets, with particular emphasis on the highly imbalanced 1-year survival prediction task. To address this issue, we propose a method that creates a pipeline of some of standard balancing techniques to increase the true positive rate. Evaluation is conducted on a colorectal cancer dataset from the SEER database. Methods: The pre-processing step consists of removing records with missing values and merging categories. The minority class of 1-year and 3-year survival tasks consists of 10% and 20% of the data, respectively. Edited Nearest Neighbor, Repeated edited nearest neighbor (RENN), Synthetic Minority Over-sampling Techniques (SMOTE), and pipelines of SMOTE and RENN approaches were used and compared for balancing the data with tree-based classifiers. Decision Trees, Random Forest, Extra Tree, eXtreme Gradient Boosting, and Light Gradient Boosting (LGBM) are used in this article. Method. Results: The performance evaluation utilizes a 5-fold cross-validation approach. In the case of highly imbalanced datasets (1-year), our proposed method with LGBM outperforms other sampling methods with the sensitivity of 72.30%. For the task of imbalance (3-year survival), the combination of RENN and LGBM achieves a sensitivity of 80.81%, indicating that our proposed method works best for highly imbalanced datasets. Conclusions: Our proposed method significantly improves mortality prediction for the minority class of colorectal cancer patients.Comment: 19 Pages, 6 Figures, 4 Table

Relationship between Motor and Mental Age in Children with Down Syndrome

Objectives: Down syndrome (DS) is the most common multiple congenital anomaly syndrome associated with a developmental disability. Children with Down syndrome have delay in both motor and mental age. This study carried out to explore relationship between mental and motor age of children with DS. Methods: A cross-sectional study was conducted on 60 participants with DS (5 to 7 years old) using randomized method of sampling based on inclusion and exclusion criteria. Mental and motor age of participants was measured by Peabody Developmental Motor Scales and Goodenough Draw A Man Test. Results: Test result was analyzed for total, gross and fine motor age and mental age. Results were interpreted by the statistical method of pearson correlation analysis. There was significant correlation between mental age and total motor age based on pearson correlation coefficient (r=0.93). Discussion: Results of the study showed that there were strong positive correlations between gross, fine and total motor age, and mental age of children with Down syndrome and suggest the hypothesis that simultaneous utilization of motor and mental practice through rehabilitation programs is more effective than mere practice

Evaluation of the expansion of umbilical cord blood derived from CD133+ cells on biocompatible microwells

Background: Hematopoietic stem cell transplantation (HSCT) is a therapeutic approach for treatment of hematological malignancies and incompatibility of Bone marrow. Umbilical cord blood (UCB) has known as an alternative for hematopoietic stem/progenitor cells (HPSC) in allogeneic transplantation. The low volume of collected samples is the main hindrance in application of HPSC derived from umbilical cord blood. So, ex vivo expansion of HPSCs is the useful approach to overcome this restriction. The goal of using this system is to produce appropriate amount of hematopoietic stem cells, which have the ability of transplantation and long term haematopoiesis. Material & Methods: In current study CD133+ cells were isolated from cord blood (CB). Isolated cells were seeded on microwells. Then expanded cells proliferation rate and ability in colony formation were assessed and finally were compared with 2 Dimensional (2D) culture systems. Results: Our findings demonstrated that CD133+ cells derived from UCB which were cultivated on microwells had significantly higher rate of proliferation in compared with routine cell culture systems. Conclusion: In Current study, it was shown that CD133+ cells’ proliferations which were seeded on PDMS microwells coated with collagen significantly increased. We hope that 3 dimensional (3D) microenvironment which mimics the 3D structure of bone marrow can solve the problem of using UCB as an alternative source of bone marrow