Artificial Intelligence-Empowered Bio-medical Applications Challenges, Solutions and Development Guidelines /
The book delves into advancements in personalized medicine, highlighting the transition from generalized treatments to tailored strategies through AI and machine learning. It first emphasizes the role of biomarkers in training predictive models and neural networks, enhancing disease diagnosis and pa...
Tallennettuna:
| Päätekijät: | , , |
|---|---|
| Yhteisötekijä: | |
| Aineistotyyppi: | Elektroninen E-kirja |
| Kieli: | englanti |
| Julkaistu: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
|
| Painos: | 1st ed. 2025. |
| Sarja: | Learning and Analytics in Intelligent Systems,
49 |
| Aiheet: | |
| Linkit: | https://doi.org/10.1007/978-3-031-90174-4 |
| Tagit: |
Lisää tagi
Ei tageja, Lisää ensimmäinen tagi!
|
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-90174-4 | ||
| 003 | DE-He213 | ||
| 005 | 20260810165431.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 250618s2025 sz | o |||| 0|eng d | ||
| 020 | |a 9783031901744 |9 978-3-031-90174-4 | ||
| 024 | 7 | |a 10.1007/978-3-031-90174-4 |2 doi | |
| 050 | 4 | |a R856-857 | |
| 072 | 7 | |a MQW |2 bicssc | |
| 072 | 7 | |a TEC059000 |2 bisacsh | |
| 072 | 7 | |a MQW |2 thema | |
| 082 | 0 | 4 | |a 610.28 |2 23 |
| 100 | 1 | |a Panagoulias, Dimitrios P. |e author. |0 (orcid)0000-0002-9421-141X |1 https://orcid.org/0000-0002-9421-141X |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Artificial Intelligence-Empowered Bio-medical Applications |h [electronic resource] : |b Challenges, Solutions and Development Guidelines / |c by Dimitrios P. Panagoulias, George A. Tsihrintzis, Maria Virvou. |
| 250 | |a 1st ed. 2025. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2025. | |
| 300 | |a 1 online resource (XXV, 287 p. 120 illus.). |b 113 illus. in color. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background color |2 onix | |
| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Learning and Analytics in Intelligent Systems, |x 2662-3455 ; |v 49 | |
| 505 | 0 | |a Introduction to AI-empowered Medical Soft [1] ware: Recent Advances and Challen -- Personalized Nutrition Applications using Biomarkers and Machine Learning -- Blood Exam Classification for Predicting Defin [1] ing Factors in Metabolic Syndrome Diagnosis using Sup [1] port Vector Machine -- Extreme Value Analysis applied in Dietary Data -- Iterative Microservices Approach for Explain [1] able and Reliable AI in Medical Application -- Challenges in Regulating and Validating AI [1] Driven Healthcar -- Framework for AI Explainability Leveraging User Acceptance and Health Literacy Models. | |
| 520 | |a The book delves into advancements in personalized medicine, highlighting the transition from generalized treatments to tailored strategies through AI and machine learning. It first emphasizes the role of biomarkers in training predictive models and neural networks, enhancing disease diagnosis and patient management. It then explores AI-driven healthcare systems, particularly the use of microservices to improve scalability and management. Additionally, it examines regulatory challenges, the need for AI explainability, and the PINXEL framework, which defines explainability requirements using the technology acceptance model (TAM) and the diffusion of innovation theory (DOI). Furthermore, the book evaluates the capabilities of large language models, including ChatGPT and GPT-4V, in medical applications, with a focus on diagnosis and structured assessments in general pathology. Lastly, it introduces an AI-powered system for primary care diagnosis that integrates language models, machine learning, and rule-based systems. The interactive AI assistants “Med/Primary AI assistant” and “Dermacen Analytica” leverage natural language processing, image analysis, and multi-modal AI to enhance patient interactions and provide healthcare professionals with high-accuracy, personalized diagnostic support. By taking a holistic approach, the book underscores the integration of AI into healthcare, aiming to support medical professionals in patient diagnosis and management with precision and adaptability. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Biomedical engineering. | |
| 650 | 0 | |a Engineering |x Data processing. | |
| 650 | 0 | |a Computational intelligence. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 1 | 4 | |a Biomedical Engineering and Bioengineering. |
| 650 | 2 | 4 | |a Data Engineering. |
| 650 | 2 | 4 | |a Computational Intelligence. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 700 | 1 | |a Tsihrintzis, George A. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 700 | 1 | |a Virvou, Maria. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031901737 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031901751 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031901768 |
| 830 | 0 | |a Learning and Analytics in Intelligent Systems, |x 2662-3455 ; |v 49 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-90174-4 |
| 912 | |a ZDB-2-ENG | ||
| 912 | |a ZDB-2-SXE | ||
| 912 | |a ZDB-2-231 | ||
| 950 | |a Engineering (SpringerNature-11647) | ||
| 950 | |a Engineering (R0) (SpringerNature-43712) | ||
| 950 | |a Focus Bundle Biological and Physical Engineering (SpringerNature-85401) | ||