Automated classification of White Blood Cells (WBCs) with Deep Learning

Usecase in Healthcare Data Intelligence

Though the WBCs account for only 1% of the human blood, they are the most important blood component as they protect against disease and illness. There are five different types of WBCs:

1. Monocytes (help break down bacteria)
2. Lymphocytes (create antibodies)
3. Neutrophils (kill and digest bacteria)
4. Basophils (body’s immune response system)
5. Eosinophils (kill parasites and cancer cells)

Classifying the WBCs with a traditional approach is time-consuming and majorly dependent on the pathologists’ efficiency. To overcome these challenges, an automated and computer-based system can be developed as they contribute to the acceleration of the analysis process and highly accurate results.

We conducted this study to classify the WBCs by leveraging Image processing and Deep Learning techniques. Our solution provides instant results that enable healthcare providers with real-time access to the data on WBCs for a speedy treatment or diagnosis of diseases like leukemia, AIDS, bacterial infections, etc.

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About Qualetics Data Machines

Data Analytics and Artificial Intelligence is growing to be an ubiquitous need in the modern enterprise ecosystem. The need for Analytics is ranging from basic Descriptive and Diagnostic Analytics to advanced Predictive, Prescriptive and Cognitive Analytics.  However, the barrier of entry is high due to expensive infrastructure and highly skilled resource requirements.

Qualetics Data Machines Inc. aims to eliminate this barrier by introducing a product that makes it easy for businesses to embrace data science and gain data intelligence.

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