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Opis
PART I: BACKGROUND
1. Market overview, growth, and why
2. Fundamental concepts (e.g. AI, ML), vocabulary
3. Technology principles (e.g. modelling, learning methods, deep learning, sparse coding, big data)
PART II: APPLICATIONS
1. Breast (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
2. Cardiovascular (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
3. Chest (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
4. Emergency (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
5. Gastrointestinal (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
6. Genitourinary (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
7. Head and neck (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
8. Musculoskeletal (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
9. Neuroradiology (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
10. Paediatric (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
11. Interventional (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
12. Nuclear (Current FDA-approved applications; existing companies; applications under development; opportunities, defined needs)
PART III: DEVELOP YOUR APPLICATION
13. Problem (ideation process, what problem are you solving, for whom, value prop, special sauce)
14. Team (who you need, roles)
15. R&D, validation process
16. Regulatory, quality, ethical, legal
PART IV: COMMERCIALIZATION
17. Routes of commercialization
18. Funding- who, how, economics, power
19. Cases studies (stories of successful rad AI ventures)
Indeks: 17221
Autor: Frank H. Netter
Promocja akademicka 2024