https://kaggle.com/paultimothymooney/blood-cells (Accessed Apr. 14, 2021). Shenggan/BCCD_Dataset: BCCD (Blood Cell Count and Detection) Dataset is a small-scale dataset for blood cells detection. Accessed: Mar. 06, 2021. [Online]. Available at https://github.com/Shenggan/BCCD_Dataset...
The data was procured from kaggle. Source:https://www.kaggle.com/paultimothymooney/blood-cells. The dataset contains 12,500 augmented images of various types of white blood cells (JPEG) with metadata in CSV form. That includes 3,000 images divided into 4 different white blood cell types (cl...
accessible athttps://www.kaggle.com/datasets/paultimothymooney/blood-cells. This dataset contains blood sample images from four types of leukocytes: Neutrophil (NE), Eosinophil (EO), Lymphocyte (LM), and Monocyte (MN). It contains a total of 12,444 images, with each leukocyte type indicated ...
They deployed the proposed approach on the Kaggle WBC images dataset and achieved significant accuracy. The study [16] proposed a multi-level CNN model for the WBC classification for four types of cell classification. At the first level, Faster R-CNN is applied for the detection of the region...
Diabetes UCI Dataset. Available online: https://www.kaggle.com/datasets/alakaaay/diabetes-uci-dataset (accessed on 4 March 2024). Yahyaoui, A.; Jamil, A.; Rasheed, J.; Yesiltepe, M. A Decision Support System for Diabetes Prediction Using Machine Learning and Deep Learning Techniques. In ...
investigated machine learning techniques for COVID-19 diagnosis through routine blood tests, using a public dataset from a Brazilian hospital. The random forest (RF) performed the best among the classifiers tested. A decision tree explainer (DTX) was utilized for localized explanations to improve ...
5.1. Dataset The dataset employed in this study is sourced from a publicly accessible collection of blood cell images on Kaggle (https://www.kaggle.com/datasets/paultimothymooney/blood-cells, accessed on 11 July 2024), consisting of 410 original high-resolution images. These original images have...
They used the C-NMC leukemia dataset from Kaggle. The C-NMC leukemia dataset is broken up into two groups: healthy and cancer cells. The results showed that SVM outperforms other algorithms with an accuracy of 90%. Kasani et al. [23] proposed an aggregated DL model to classify leukemic ...
The model was evaluated using a dataset from Kaggle containing 12,444 images of various types of WBCs. The results indicated that the model achieved an accuracy of 98.84%, precision of 99.33%, sensitivity of 98.85%, and specificity of 99.61%. Jung et al. [17] proposed a CNN-based method...
Acute lymphoblastic leukemia (ALL) is a lethal blood cancer that is characterized by an abnormal increased number of immature lymphocytes in the blood or bone marrow. For effective treatment of ALL, early assessment of the disease is essential. Manual examination of stained blood smear images is ...