Artificial intelligence for medicine : an applied reference for methods and applications /
"Introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and t...
Furkejuvvon:
| Eará dahkkit: | , , , , , |
|---|---|
| Materiálatiipa: | Elektrovnnalaš E-girji |
| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
London :
Academic Press, an imprint of Elsevier,
[2024]
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| Ráidu: | Advanced studies in complex systems.
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| Fáttát: | |
| Liŋkkat: | ScienceDirect |
| Fáddágilkorat: |
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Sisdoallologahallan:
- 1. Artificial intelligence in cancer research and precision medicine
- 2. Machine learning in computational pathology through self-supervised learning and vision transformers
- 3. Artificial intelligence in small-molecule drug delivery
- 4. AI/ML and drug repurposing in lung cancer: State of the art and potential roles for retinoids
- 5.Artificial intelligence and digital worlds: New frontiers of integration between AI and other technological tools
- 6. The dual path of the technology acceptance model: An application of machine learning cardiotocography in delivery rooms
- 7. Artificial intelligence in diagnostic and predictive pathology
- 8. Artificial intelligence in the oncology workflow: Applications, limitations, and future perspectives
- 9. SOK: Application of machine learning models in child and youth mental health decision-making
- 10. Cancer detection in hyperspectral imagery using artificial intelligence: Current trends and future directions
- 11. Global research trends of Artificial Intelligence and Machine Learning applied in medicine: A bibliometric analysis (2012-2022)
- 12. Ethics and regulations for AI in radiology
- 13. The role of artificial intelligence in radiology and interventional oncology
- 14. The multiomics revolution in the era of deep learning: Allies or enemies?
- 15. Artificial intelligence in behavioral health economics: Considerations for designing behavioral studies
- 16. Artificial intelligence and medicine: A psychological perspective on AI implementation in healthcare context
- 17. AI for outcome prediction in Radiation Oncology: The present and the future
- 18. Artificial intelligence in neurologic disease
- 19. Should I trust this model? Explainability and the black box of artificial intelligence in medicine.