1.

Record Nr.

UNIORUON00149855

Autore

MAHETA, Yashodhara

Titolo

Sakshatkarane raste / Yashodhara Maheta

Pubbl/distr/stampa

Amadabada, : Gurjara Gramtharatna Karyalaya, 1972

Descrizione fisica

151 p. ; 18 cm

Classificazione

SI I

Lingua di pubblicazione

Gujarati

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910710773503321

Autore

Kaiser Debra L

Titolo

Ceramics Division FY 2004 programs and accomplishments / / Debra L. Kaiser; Ronald G. Munro

Pubbl/distr/stampa

Gaithersburg, MD : , : U.S. Dept. of Commerce, National Institute of Standards and Technology, , 2004

Descrizione fisica

1 online resource

Collana

NISTIR ; ; 7124

Altri autori (Persone)

KaiserDebra L

MunroR. G (Ronald Gordon)

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

2004.

Contributed record: Metadata reviewed, not verified. Some fields updated by batch processes.

Title from PDF title page.

Nota di bibliografia

Includes bibliographical references.



3.

Record Nr.

UNINA9910985677503321

Autore

Srivastava Ruby

Titolo

Artificial Intelligence Multiomics in Precision Oncology

Pubbl/distr/stampa

Newcastle-upon-Tyne : , : Cambridge Scholars Publishing, , 2023

©2023

ISBN

9781527500891

9781443895200

Edizione

[1st ed.]

Descrizione fisica

1 online resource (517 pages)

Disciplina

616.9940028563

Soggetti

Artificial intelligence

Precision medicine

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Intro -- Dedication -- Table of Contents -- Preface -- Acknowledgements -- Chapter 1 -- Chapter 2 -- Chapter 3 -- Chapter 4 -- Chapter 5 -- Chapter 6 -- Chapter 7 -- Chapter 8 -- Chapter 9 -- Chapter 10 -- Chapter 11 -- Chapter 12 -- Chapter 13.

Sommario/riassunto

Advances in next-generation technology (NGS) coupled with a deep understanding of cancer biology have promoted the rational design of target therapy towards precision oncology. Artificial Intelligence (AI)-integrated machine learning techniques are also increasingly used today to tackle the challenges of scalability and high dimensionality data and to transform multiomics data into clinically actionable knowledge. AI tools are used to support clinical decision making and improve clinical efficiency, while delivering safe and high value care. This book provides comprehensive analysis of such techniques and advancements of AI-based clinical cancer research in the improvement of cancer prognosis and diagnosis, resulting in enhanced prediction rates and survival of cancer patients.