• About Dataset Safa S. Abdul-Jabbar, Alaa k. Farhan

• Context This is the first Dataset for various ordinary patients in Iraq. The Dataset provides the patients’ Cell Blood Count test information that can be used to create a Hematology diagnosis/prediction system. Also, this Data was collected in 2022 from Al-Zahraa Al-Ahly Hospital. These data can be cleaned & analyzed using any programming language because it is provided in an excel file that can be accessed and manipulated easily. The user just needs to understand how rows and columns are arranged because the data was collected as images(CBC images) from the laboratories and then stored the extracted data in an excel file.  Content This Dataset contains 500 rows. For each row (patient information), there are 21 columns containing CBC test features that can be described as follows:

• ID: Patients Identifier

• WBC: White Blood Cell, Normal Ranges: 4.0 to 10.0, Unit: 10^9/L.

• LYMp: Lymphocytes percentage, which is a type of white blood cell, Normal Ranges: 20.0 to 40.0, Unit: %

• MIDp: Indicates the percentage combined value of the other types of white blood cells not classified as lymphocytes or granulocytes, Normal Ranges: 1.0 to 15.0, Unit: %

• NEUTp: Neutrophils are a type of white blood cell (leukocytes); neutrophils percentage, Normal Ranges: 50.0 to 70.0, Unit: %

• LYMn: Lymphocytes number are a type of white blood cell, Normal Ranges: 0.6 to 4.1, Unit: 10^9/L.

• MIDn: Indicates the combined number of other white blood cells not classified as lymphocytes or granulocytes, Normal Ranges: 0.1 to 1.8, Unit: 10^9/L.

• NEUTn: Neutrophils Number, Normal Ranges: 2.0 to 7.8, Unit: 10^9/L.

• RBC: Red Blood Cell, Normal Ranges: 3.50 to 5.50, Unit: 10^12/L

• HGB: Hemoglobin, Normal Ranges: 11.0 to 16.0, Unit: g/dL

• HCT: Hematocrit is the proportion, by volume, of the Blood that consists of red blood cells, Normal Ranges: 36.0 to 48.0, Unit: %

• MCV: Mean Corpuscular Volume, Normal Ranges: 80.0 to 99.0, Unit: fL

• MCH: Mean Corpuscular Hemoglobin is the average amount of haemoglobin in the average red cell, Normal Ranges: 26.0 to 32.0, Unit: pg

• MCHC: Mean Corpuscular Hemoglobin Concentration, Normal Ranges: 32.0 to 36.0, Unit: g/dL

• RDWSD: Red Blood Cell Distribution Width, Normal Ranges: 37.0 to 54.0, Unit: fL

• RDWCV: Red blood cell distribution width, Normal Ranges: 11.5 to 14.5, Unit: %

• PLT: Platelet Count, Normal Ranges: 100 to 400, Unit: 10^9/L

• MPV: Mean Platelet Volume, Normal Ranges: 7.4 to 10.4, Unit: fL

• PDW: Red Cell Distribution Width, Normal Ranges: 10.0 to 17.0, Unit: %

• PCT: The level of Procalcitonin in the Blood, Normal Ranges: 0.10 to 0.28, Unit: %

• PLCR: Platelet Large Cell Ratio, Normal Ranges: 13.0 to 43.0, Unit: %

• Acknowledgements We thank the entire Al-Zahraa Al-Ahly Hospital Hospital team, especially the hospital manager, for cooperating with us in collecting this data while maintaining patients' confidentiality.

Dataset Description:

This dataset is a comprehensive collection of Complete Blood Count (CBC) images, meticulously organized to support machine learning and deep learning projects, especially in the domain of medical image analysis. The dataset's structure ensures a balanced and systematic approach to model development, validation, and testing.

Dataset Breakdown:

• Training Images: 300
• Validation Images: 60
• Test Images: 60
• Annotations: Detailed annotations included for all images

Overview:

The Complete Blood Count (CBC) is a crucial test used in medical diagnostics to evaluate the overall health and detect a variety of disorders, including anemia, infection, and many other diseases. This dataset provides a rich source of CBC images that can be used to train machine learning models to automate the analysis and interpretation of these tests.

Data Composition:

1. Training Set:

   • Contains 300 images
   • These images are used to train machine learning models, enabling them to learn and recognize patterns associated with various blood cell types and conditions.

2. Validation Set:

   • Contains 60 images
   • Used to tune the models and optimize their performance, ensuring that the models generalize well to new, unseen data.

3. Test Set:

   • Contains 60 images
   • Used to evaluate the final model performance, providing an unbiased assessment of how well the model performs on new data.

Annotations:

Each image in the dataset is accompanied by detailed annotations, which include information about the different types of blood cells present and any relevant diagnostic features. These annotations are essential for supervised learning, allowing models to learn from labeled examples and improve their accuracy and reliability.

Key Features:

• High-Quality Images: All images are of high quality, making them suitable for a variety of machine learning tasks, including image classification, object detection, and segmentation.
• Comprehensive Annotations: Each image is thoroughly annotated, providing valuable information that can be used to train and validate models.
• Balanced Dataset: The dataset is carefully balanced with distinct sets for training, validation, and testing, ensuring that models trained on this data will be robust and generalizable.

Applications:

This dataset is ideal for researchers and practitioners in the fields of machine learning, deep learning, and medical image analysis. Potential applications include: - Automated CBC Analysis: Developing algorithms to automatically analyze CBC images and provide diagnostic insights. - Blood Cell Classification: Training models to accurately classify different types of blood cells, which is critical for diagnosing various blood disorders. - Educational Purposes: Using the dataset as a teaching tool to help students and new practitioners understand the complexities of CBC image analysis.

Usage Notes:

• Data Augmentation: Users may consider applying data augmentation techniques to increase the diversity of the training data and improve model robustness.
• Preprocessing: Proper preprocessing, such as normalization and noise reduction, can enhance model performance.
• Evaluation Metrics: It is recommended to use standard evaluation metrics such as accuracy, precision, recall, and F1-score to assess model performance.

Conclusion:

This CBC dataset is a valuable resource for anyone looking to advance the field of automated medical diagnostics through machine learning and deep learning. With its high-quality images, detailed annotations, and balanced composition, it provides the necessary foundation for developing accurate and reliable models for CBC analysis.

The complete blood count (CBC) dataset contains 360 blood smear images along with their annotation files splitting into Training, Testing, and Validation sets. The training folder contains 300 images with annotations. The testing and validation folder both contain 60 images with annotations. We have done some modifications over the original dataset to prepare this CBC dataset where some of the image annotation files contain very low red blood cells (RBCs) than actual and one annotation file does not include any RBC at all although the cell smear image contains RBCs. So, we clear up all the fallacious files and split the dataset into three parts. Among the 360 smear images, 300 blood cell images with annotations are used as the training set first, and then the rest of the 60 images with annotations are used as the testing set. Due to the shortage of data, a subset of the training set is used to prepare the validation set which contains 60 images with annotations.

The dataset contains fake and real news. There are 16898 unique rows that points out the numbers of news as well. The dataset is merged from two datasets one is from different source of CBC news (link: https://zenodo.org/record/4722470) and other is from different web portals (link: https://zenodo.org/record/4282522).

Data Description:

Text: Text contains the news that is either fake or real.

Outcome: Contains either fake or real which is the status of the news.

This dataset is about books. It has 9 rows and is filtered where the book publisher is CBC Publishing. It features 7 columns including author, publication date, language, and book publisher.

Cbc Complete2_duplicate

## Overview

Cbc Complete2_duplicate is a dataset for object detection tasks - it contains Blood Cell C2o1 annotations for 1,106 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Our Customer Service Centre runs regular surveys to measure overall satisfaction with the service received. Each survey operates for a month and aims to record the views of as many customers as possible.

Cbc

## Overview

Cbc is a dataset for object detection tasks - it contains Cells annotations for 360 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

This measure reports the percentage of offenders who are currently living in residential facilities supervised by Iowa Community Based Corrections who have or are working towards a post-secondary education degree. It includes offenders where the highest level of education completed is one of the following: In College, Freshman level college, Sophomore level college, Junior level college, Vocational/Technical Student, Technical Training Completion, Vocational Program/Technical Certificate, Associate's Degree, Bachelor's Degree, Master's Degree, or Doctorate.

Dataset Card for Content Behavior Corpus

The Content Behavior Corpus (CBC) dataset, consisting of content and the corresponding receiver behavior.

  Dataset Details

The progress of Large Language Models (LLMs) has largely been driven by the availability of large-scale unlabeled text data for unsupervised learning. This work focuses on modeling both content and the corresponding receiver behavior in the same space. Although existing datasets have trillions of content… See the full description on the dataset page: https://huggingface.co/datasets/behavior-in-the-wild/content-behavior-corpus.

Analysis of ‘Anemia Diagnosis Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/saurabhshahane/anemia-diagnosis-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

This data set presents the prevalence of different types of Anemia including it’s severity and association with age and gender of the study population with CBC data set parameters as variables. We generated dataset from complete blood count test performed by Hematology analyzer to determine the prevalence of different types of Anemia treated at the Eureka diagnostic center in Lucknow, India. All the procedures for the CBC test were done following standard operating protocols defined for the Hematology analyzer. For CBC investigation, 400 patient samples were randomly selected to compute the dataset from the patients who visited the Eureka diagnostic center in Lucknow for various clinical examinations. The diagnostic center performs 4 – 8CBC investigations a day on average. During the data collection period between September 2020 to December 2020, 1000 CBC investigations were performed, out of which 400 random samples were selected. We included adult males and females who are not pregnant and older than 15 years of age in the study population. Infants, young children less than 10 years old and pregnant women were excluded from the study due to various factors like variable CBC test values and other factors. After excluding the above stated persons from the randomly chosen sample of 400 patients, we were left with 364 patients in the final data set.

Acknowledgements

Vohra, Rajan; pahareeya, jankisharan; Hussain, Abir (2021), “Complete Blood Count Anemia Diagnosis”, Mendeley Data, V1, doi: 10.17632/dy9mfjchm7.1

--- Original source retains full ownership of the source dataset ---

CbcSingleClass

## Overview

CbcSingleClass is a dataset for object detection tasks - it contains Circle annotations for 360 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Dataset Card for Competency-Based Curriculum (CBC) Dataset - Kenya

This dataset card describes a curated collection of data extracted from online sources covering Kenya’s Competency-Based Curriculum (CBC). It is intended for educational research, policy analysis, and machine learning tasks focused on curriculum understanding, content classification, and educational resource generation.

  Dataset Details





  Dataset Description

This dataset contains structured and… See the full description on the dataset page: https://huggingface.co/datasets/JK-TK/webCbdataset.

HCT: Hematocrit, MCV: Mean corpuscular value, NRBC: Nucleated red blood cells, WBC: White blood cells. (XLSX)

This measure reports the percentage of offenders in residential facilities supervised by Iowa Community Based Corrections who have less than a HS diploma or equivalent. It includes offenders where the highest level of education completed is First through Twelfth, No Diploma/No Certificate, Now Attending, or Unknown.

Detector_cbc_yolov8

## Overview

Detector_cbc_yolov8 is a dataset for object detection tasks - it contains Cancer annotations for 4,000 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

BCCD FINALS

## Overview

BCCD FINALS is a dataset for object detection tasks - it contains BCCD annotations for 210 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Anemia is still a significant public health problem in Africa including Ethiopia. It has multifaceted causes from nutritional deficiency and infections to autoimmune diseases to genetic factors. Iron deficiency (ID) is the leading cause of anemia and is estimated to contribute to 42% of cases in children aged under five years [1]. In its most recent nutritional anemias prevention and control tool, World Health Organization acknowledged the proportion of anemia attributable to ID could be lower than the previously assumed 50% [2]. A national micronutrient survey in Ethiopia reported that iron deficiency anemia (IDA) accounts for 35.8% of anemia cases using sTfR (soluble serum transferrin receptor) among preschool age (6 - 59 months) children [3]. There are other important causes of anemia among preschool and school-age children including folate and vitamin B12 deficiency, acute and chronic infection/inflammation and parasitic infestation. However, evidence on the types of anemia (other than iron deficiency) that contribute to the remaining large portion is not well established. This dataset tries to determine the magnitude and types of anemia in relation to age based on red blood cell (RBC) morphology among 6-59 months old children who visited Hawassa University Comprehensive and Specialized Hospital (HUCRH). Electronic hematological records of all children 6-59 months who visited Hawassa University Comprehensive and Specialized Hospital (HUCRH) for health service and medical care between May 2017 to May 2019 were retrieved from the hospital laboratory. The hematological data retrieved included age, sex and town/city of residence and results of Complete Blood Count (CBC) tests including hemoglobin, hematocrit, RBC count and RBC indices (mean corpuscular volume [MCV], mean corpuscular hemoglobin [MCH] and red cell distribution width [RDW]. HUCRH used CELL-DYN Ruby, SYSMEX and Mindray hematology analyzers to carry out CBC tests. As per WHO guideline, hemoglobin (Hgb) values were adjusted for altitude and anemia was defined as hemoglobin values of < 11.0g/dl. Severity of anemia was categorized as mild, moderate and severe by hemoglobin levels of 10-10.9g/dl, 7-9.9 g/dl and <7 g/dl respectively. Red blood cell indices used to classify anemia were MCV, MCH and RDW. In this dataset, iron deficiency anemia is defined as microcytic (low MCV) and hypochromic (low MCH) anemia with high red cell distribution width (RDW).

Invasive species offer ecologists the opportunity to study the factors governing species distributions and population growth. The Eurasian Collared-Dove (Streptopelia decaocto) serves as a model organism for invasive spread because of the wealth of abundance records and the recent development of the invasion. We tested whether a set of environmental variables were related to the carrying capacities and growth rates of individual populations by modeling the growth trajectories of individual populations of the Collared-Dove using Breeding Bird Survey (BBS) and Christmas Bird Count (CBC) data. Depending on the fit of our growth models, carrying capacity and growth rate parameters were extracted and modeled using historical, geographical, land cover and climatic predictors. Model averaging and individual variable importance weights were used to assess the strength of these predictors. The specific variables with the greatest support in our models differed between data sets, which may be the result of temporal and spatial differences between the BBS and CBC. However, our results indicate that both carrying capacity and population growth rates are related to developed land cover and temperature, while growth rates may also be influenced by dispersal patterns along the invasion front. Model averaged multivariate models explained 35–48% and 41–46% of the variation in carrying capacities and population growth rates, respectively. Our results suggest that widespread species invasions can be evaluated within a predictable population ecology framework. Land cover and climate both have important effects on population growth rates and carrying capacities of Collared-Dove populations. Efforts to model aspects of population growth of this invasive species were more successful than attempts to model static abundance patterns, pointing to a potentially fruitful avenue for the development of improved invasive distribution models.

Raw data on complete blood count and coagulation test, updated on 18 Oct, 2023. The establishment and use of the database were approved Ethical committee of Hung Vuong Hospital, Vietnam. The data were collected from the pregnant women who visited obstetrics clinic from June 2023 to August 2023. Data on demographic factors, gestational age, vital signs, laboratory measurements were systematically collected.