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license: mit |
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# 🚀 AI Project Data Card |
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## Overview 📊 |
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- Value of State and Country NPI Dataset 🌎 |
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- Provides comprehensive insights into healthcare providers across various regions. |
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- Enhances data accuracy and availability for medical research and policy making. |
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- NUCC Specialty File 🔍 |
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- Delivers detailed descriptions of physician specialties. |
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- Includes unique codes for over 100 specialties, facilitating standardized data analysis. |
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# This study into AI discovers cross references from provider data and poses search technology to make it easier to build perrsonalized information on physicians for AI scientists and patients to begin to undderstand how we can assist in building relationships. |
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There are a number of assets here: |
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1. app.py and requirements.txt for pre processor which curates state and country files with high fidelity and distilledd knowledge using the NPI registry and NUCC taxonomy at scale compiling over 9GB data into a curated data strategy. |
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2. MN.csv sample state - This provides a snapshot of just Minnesota which is used to Test AI. |
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3. Zip file with all. To reuse the state and country datasets a zip file is provided to get all the ccurated data using one file. My thoughts are this later becauses the standard for contextual 'brain' files which represent data context around a subject. |
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4. NUCC specialty file which is the guide to medical and various provider specialties. The description of these is a good keyword prompt data source for understanding specialties. |
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# Pain / Joy / Superpower |
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1. Pain - When looking for a medical procedure provider it is not easy to know what to look for or who in your area may match. |
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2. Joy - A new use might be able to consider search needs of patient in keywords, then find personalized physician relationships available in an area. |
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3. Superpower - This will help patients and referral specialists find personalized optimal physician sets for condition sets ' |
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- an obstetrician, surgeon, or physician that might be optimal for a given patient given that they align to multiple patient requirements. |
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- a test case for this is analyzing the treatments available for cancer which might require multi specialty PCPs. |
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- like a dermatologist that also can perform surgery for cheap since one physician might match the two specialties. |
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# Sources: |
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1. NUCC Taxonomy: https://www.nucc.org/index.php/code-sets-mainmenu-41/provider-taxonomy-mainmenu-40 |
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2. NPI Registry updated monthly: https://download.cms.gov/nppes/NPI_Files.html |
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## Physician Lists Library 📚 |
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- Features over 100 state and country-based lists. |
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- Offers contact details and provider specialty references, aiding in network expansion and collaboration. |
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## Licensing Boards and Certification Exams 📝 |
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- Covers all types of physicians and healthcare professionals. |
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- Medical (USMLE) 🏥 |
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- Dental (NBDE) 🦷 |
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- Nursing (NCLEX) 🩺 |
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- Pharmacy (NAPLEX) 💊 |
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- Plus more for comprehensive coverage. |
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## Applications and Use Cases 💡 |
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- Building Libraries of Specialists for MoE Information 🏛️ |
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- Supports the creation of specialized knowledge bases. |
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- Facilitates targeted outreach and collaboration among healthcare professionals. |
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- Enhancing Healthcare Directories and Networks 🌐 |
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- Improves the accuracy and reach of healthcare directories. |
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- Enables patients and providers to connect more efficiently. |
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## Conclusion and Next Steps 🛣️ |
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- This dataset and its associated libraries offer vast potential for healthcare improvement. |
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- Encourages further exploration and development of AI-driven applications in healthcare. |
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_For more details on accessing and utilizing these resources, please refer to the project documentation and code repositories._ |
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