Ron Fridman "Майбутнє коп'ютеризованого здоров'я. Яким чином штучний інтелект застосовуєтья в роботі з MedTech"
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Ron Fridman "Майбутнє коп'ютеризованого здоров'я. Яким чином штучний інтелект застосовуєтья в роботі з MedTech"
- 2. Why I am here? Tech Entrepreneur | CEO of Mawi Solutions Machine learning expert SingularityU Kyiv Chapter AI Lecturer Preventive Medicine evangelist
- 19. Business case 1 How to ensure USA government using AI?
- 21. Atrial fibrillation features in the heart biomechanics Normal Sinus Rhythm Atrial Fibrillation Rhythm
- 22. Atrial fibrillation features on the ECG
- 32. Atrial fibrillation features on the ECG
- 34. Business case 2 How AI can detect stress and why it is important?
- 36. Body resources, daily cycle
- 37. Weekly cycle
- 39. If only we could listen to our hearts... But in order to do it we need to understand heart language.
- 40. AI and wearables combined helps us to translate the messages from our body
- 41. Business case 3 How to be the first in new market? – Just create this market!
- 45. From To
- 47. Can AI and heart data estimate your biological age?
- 49. Thank you for attention! E-mail: ron@mawi.band FB: www.fb.com/ronfri
Notas del editor
- Electrocardiogram Photoplethysmography
- As methods to learn patterns from data become more complex, they become harder to interpret. Deep learning represents the latest in this trend; it gives state-of-the-art results in several areas of machine learning, but its uninterpretable “black box” nature is a major problem. Say you train a model to predict which DNA mutations cause a disease. If your model performs well, it has likely discovered patterns that we ourselves would like to understand, which is not so easy if the model is a black box. The goal of our research is the make deep learning more interpretable so that we can have our powerful models and also gain insight into why they work.
- Я тебе нарисую Chain of decisions
- Я тебе нарисую Chain of decisions
- Я тебе нарисую Chain of decisions