Comprehensive Dataset Profile of In Vitro Fertilization (IVF) Clinical and Embryological Data

The In Vitro Fertilisation (IVF) dataset comprised 5,000 patient records with 20 input variables, including clinical, laboratory, and embryological characteristics. The output field indicates implantation success, classified into two groups (0 and 1): 0 for failed implantation and 1 for successful implantation. Preprocessing and normalisation were applied to the dataset to enhance the quality of the data and balance the contributions of all features in predictive modelling. To avoid the dominance of particular features and numerical instability in the optimisation process, key variables were normalised to 0-1, such as patient age, AMH levels, number of oocytes retrieved, sperm quality, embryo grading and implantation outcomes. The missing values were reviewed. Coding categorical data into numerical data for machine learning was performed.