AI Analysis for Enterprise
Evolution of artificial intelligence in healthcare: a 30-year bibliometric study
This study analyzes 22,950 documents on AI in healthcare from 1993-2023, revealing an explosive growth trend (26.97% annual growth rate). The US and China lead research, with Harvard as the top institution. Emerging topics like COVID-19 and drug discovery are prominent, and ChatGPT is a recent key focus, dominating top-cited papers in 2023. The research highlights the increasing integration and profound applications of AI in medicine, emphasizing the need for international collaboration and enhanced understanding for future innovations.
Key Metrics from the Study
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Annual Growth Rate (1993-2023)
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Total Documents Analyzed
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Average Citations Per Document
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Examine the quantitative growth and key trends in AI research within healthcare over the past three decades, identifying leading countries, institutions, and emerging topics.
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Average Annual Growth Rate (1993-2023)
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Publications in 2023
| Country | Key Contributions |
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| United States |
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| China |
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| India |
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| United Kingdom |
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Delve into the specific applications of AI technologies within healthcare, from risk assessment to personalized medicine and drug discovery, including the impact of large language models like ChatGPT.
AI in Healthcare: Core Applications
Risk Assessment & Early Intervention
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Diagnosis & Treatment Planning
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Chronic Disease Management
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Drug Development & Therapies
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Medical Imaging Analysis
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Patient Data Management
ChatGPT's Impact in Medical Research (2023)
The five most cited publications in 2023 were all related to ChatGPT, highlighting its transformative potential. Applications include:
- Facilitating systematic reviews and evidence synthesis.
- Assisting physicians in understanding patient conditions.
- Generating initial drafts for medical writing and editing.
- Supporting medical education and teaching strategy adjustments.
Advanced AI ROI Calculator
Quantify the potential return on investment for integrating AI into your enterprise.
Your AI Implementation Roadmap
A phased approach to integrate AI strategically and maximize long-term benefits.
Discovery & Strategy
Initial consultation and needs assessment, identifying key AI opportunities specific to your enterprise. (~2-4 weeks)
Pilot Program Development
Design and implement a targeted AI pilot in a specific healthcare domain (e.g., diagnostic support, patient management). (~3-6 months)
Scalable Integration
Expand successful pilot programs across the enterprise, ensuring robust data pipelines and system interoperability. (~6-12 months)
Performance Optimization & Training
Continuous monitoring, fine-tuning of AI models, and comprehensive training for medical professionals and staff. (~Ongoing)
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