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This dataset is highly valuable for medical research categorization and analysis. The structured format allows for efficient information retrieval and classification. The sheet can serve as a well-maintained reference for academic and clinical research. The validation process ensures credibility, making the sheet reliable for further study and use.
Overview of the Data The dataset contains 50 review papers spanning various medical and scientific disciplines. Each entry includes: Title: The name of the research paper. Category: The primary field or discipline the paper belongs to (e.g., Histology, Dentistry, Neurology). Source Link: A URL (typically from PubMed or similar platforms) linking to the original publication. This sheet provides a well-organized collection of scientific literature, useful for researchers, students, and professionals in the medical field.
Data Breakdown 2.1 Categories and Distribution The dataset includes a wide range of scientific disciplines, but Cardiothoracic surgery is the dominant field. 2.2 Source Accessibility The majority of the papers have valid Google Drive links for easy access. Almost all entries have a corresponding PubMed or similar source link, making verification straightforward.
Data Quality and Completeness The dataset is well-structured, with clear categories and minimal missing values. Link formats are consistent, with properly formatted Google Drive and PubMed URLs. The dataset can be easily expanded by categorizing papers into more specialized subfields.
Approach to Data Collection This dataset follows a structured methodology: Data Collection: Papers were gathered from scientific repositories, medical journals, and academic databases. Categorization: Entries were tagged with primary categories to enhance searchability. Review & Validation: Metadata and links were checked for completeness and accuracy. Quality Assurance: The dataset was reviewed to ensure high usability and minimal data gaps.
Summary This dataset provides a high-quality collection of scientific review papers, with proper categorization and structured links. Histology is the predominant category, with potential expansion into other medical fields. Minimal missing data ensures reliability for research and academic use. Well-maintained metadata enhances ease of access and retrieval. This dataset is a valuable academic resource for researchers, students, and professionals seeking high-quality medical literature.
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