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Hereditary Illness Classification Data
Patient Health Records & Digital Health
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About
This collection of records focuses on medical information pertaining to children diagnosed with genetic disorders. Given the increasing incidence of hereditary illnesses—often linked to a lack of understanding regarding genetic testing—this data is highly relevant for predictive modelling. The primary objective is enabling the prediction of a patient’s specific genetic disorder and its corresponding subclass.
Columns
- Patient Id: Serves as the unique identification number assigned to each individual patient record.
- Genetic Disorder: Identifies the type of genetic disorder present, such as Mitochondrial genetic inheritance disorders or Multifactorial genetic inheritance disorders.
- Disorder Subclass: Provides further specificity by representing the subclass of the identified disorder, examples include Leber's hereditary optic neuropathy.
Distribution
The structure includes three key columns detailing patient medical conditions. The data is suitable for machine learning classification tasks. Although a specific count of total rows is not available, the sample data illustrates that records include valid entries for all fields. Data files are typically provided in CSV format.
Usage
This data is designed for advanced analytical applications, primarily focusing on classification models. Ideal uses include developing algorithms (e.g., using XGBoost) for predicting a patient's genetic disorder type and subclass. It is also valuable for research aimed at understanding the patterns associated with hereditary illnesses.
Coverage
The dataset focuses specifically on medical records concerning children affected by genetic disorders. The scope includes details about the diagnosis and specific subclass of the ailment. Geographic location and specific time range details are not available.
License
CC0: Public Domain
Who Can Use It
- Machine Learning Engineers: To train and evaluate models capable of predicting medical diagnoses based on patient information.
- Bioinformaticians: For analysing the distribution and types of genetic ailments, such as Mitochondrial or Multifactorial inheritance disorders.
- Data Science Students: To practice classification problems within a critical healthcare domain.
Dataset Name Suggestions
- Paediatric Genetic Disorder Predictor
- Hereditary Illness Classification Data
- Children's Genetic Ailments Record
Attributes
Original Data Source: Hereditary Illness Classification Data
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