Artificial Intelligence in Healthcare, Kartoniert / Broschiert
Artificial Intelligence in Healthcare
- Third International Conference, AIiH 2026, London, UK, August 26-28, 2026, Proceedings, Part I
(soweit verfügbar beim Lieferanten)
- Herausgeber:
- Hao Ni, Daniele Cafolla
- Verlag:
- Springer, 08/2026
- Einband:
- Kartoniert / Broschiert
- Sprache:
- Englisch
- ISBN-13:
- 9783032353863
- Artikelnummer:
- 12911596
- Umfang:
- 660 Seiten
- Gewicht:
- 984 g
- Maße:
- 235 x 155 mm
- Stärke:
- 36 mm
- Erscheinungstermin:
- 12.8.2026
- Serie:
- Lecture Notes in Computer Science - Band 16875
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
Weitere Ausgaben von Artificial Intelligence in Healthcare |
Preis |
|---|---|
| Buch, Kartoniert / Broschiert, Englisch | EUR 81,04* |
Klappentext
This volume set, LNCS 16875-16877, constitutes the refereed proceedings of the third International Conference on Artificial Intelligence in Healthcare, AIiH 2026, held in London, UK, during August 26--28, 2026. The 101 full papers included in these proceedings were carefully reviewed and selected from 172 submissions. The papers were organized in topical sections as follows:
Part I: Ethics of AI in healthcare; Patient data and privacy; Machine and deep learning approaches for health data; Predictive Analytics in Healthcare; AI driven early diagnosis and prevention; and AI driven proactive care and predictive intervention;
Part II: Trustworthy AI for Healthcare in Resource-Constrained Settings; From Explainability to Accountability; Multimodal Generative AI in Healthcare; AI led personalised healthcare; AI in Pharmacology: drug discovery and drug development; Intelligent Systems & Robotics for Advanced Healthcare Solutions; Ambient Assisted Living Technology for Personalised Healthcare; and AI Innovations in Autism Diagnosis;
Part III: Medical image analysis and processing; AI-aided medical imaging; AI in mental health; AI in proactive health management; Healthcare workflow optimisation and automation; and DoRa-PVS Challenge: The Domain Randomisation Challenge for Perivascular Space Segmentation.