AED
UAD Dirham
Code: AED
Self Paced
AI-Powered Digital Pathology
Transforming Diagnostics with Deep Science AI: From Pixels to Prognosis
Early access to e-LMS included
About This Course
The integration of artificial intelligence into pathology represents a transformative shift in medical diagnostics. This program offers a deep science learning experience, focusing on AI model development, training, interpretability, and deployment within clinical workflows. Participants will be exposed to cutting-edge practices in transfer learning, ensemble modeling, and explainable AI (XAI) for pathology, ensuring a robust understanding of how technology augments traditional diagnostic tools.
Over four weeks, learners will explore regulatory compliance, ethical challenges, and medico-legal issues, balanced with practical case studies in oncology and dermatopathology. The course also covers future trends like federated learning and multi-modal imaging. This program is designed for those passionate about the future of medical diagnostics and innovation in healthcare.
Aim
To equip participants with comprehensive knowledge and practical expertise in building, validating, and deploying AI models for digital pathology, integrating ethical and regulatory frameworks, and exploring real-world clinical applications through hands-on learning and expert insights.
Program Objectives
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Understand the principles of AI model development in digital pathology
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Gain hands-on experience in CNN training, optimization, and transfer learning
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Analyze regulatory and ethical implications in AI diagnostics
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Examine real-world case studies and clinical deployment insights
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Explore future technologies and career pathways in AI-driven healthcare
Program Structure
Week 1: Developing AI Models for Pathology
- Data preparation, model selection, validation
- CNN training and optimization
- Transfer learning, ensemble models, XAI
- Clinical workflow integration
- Deployment challenges
Week 2: Regulatory and Ethical Considerations
- Regulatory compliance and approvals
- Ethical issues in AI diagnostics
- Model interpretability and transparency
- Bias and fairness management
- Risk and medico-legal aspects
Week 3: Case Studies and Applications
- AI applications in oncology
- AI in dermatopathology
- Digital diagnostics integration
- Industry expert panel discussions
- Clinical deployment insights
Week 4: Future Trends and Closure
- Multi-modal imaging and federated learning
- Future of AI in medical imaging
- Career and research opportunities
- Networking and program closure
Who Should Enrol?
- Undergraduate degree in Life Sciences, Biomedical Engineering, Pathology, Computer Science, or related fields.
- Medical professionals, data scientists, and AI/ML engineers exploring healthcare.
- Individuals with a keen interest in deep science innovation and digital health technologies.
Program Outcomes
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Build and validate AI models for digital pathology
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Navigate the ethical and regulatory framework for AI in diagnostics
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Analyze and interpret deep learning model outputs
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Integrate AI tools into clinical workflows
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Prepare for careers in AI-powered medical diagnostics
Fee Structure
Standard: ₹8,998 | $170
Discounted: ₹4499 | $85
We accept 20+ global currencies. View list →
What You’ll Gain
- Full access to e-LMS
- Real-world dry lab projects
- 1:1 project guidance
- Publication opportunity
- Self-assessment & final exam
- e-Certificate & e-Marksheet
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Publication Opportunity
Get published in a prestigious open-access journal.
Centre of Excellence
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Networking & Learning
Connect with global researchers and mentors.
Global Recognition
Worth ₹20,000 / $1,000 in academic value.
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