1.

Record Nr.

UNINA9910790663403321

Autore

Gardner Howard

Titolo

The app generation [[electronic resource] ] : how today's youth navigate identity, intimacy, and imagination in a digital world / / Howard Gardner and Katie Davis

Pubbl/distr/stampa

New Haven : , : Yale University Press, , 2013

ISBN

0-300-19918-X

Descrizione fisica

1 online resource (257 p.)

Classificazione

PSY004000SOC047000SOC052000TEC052000

Altri autori (Persone)

DavisKatie (Assistant professor)

Disciplina

004.67/80835

Soggetti

Internet and youth

Youth

Technology and youth

Identity (Psychology)

Creative ability in adolescence

Application software

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Preface -- Introduction -- Talk ab out technology -- Unpacking the generations : from biology to culture to technology -- Personal identity in the age of the app -- Apps and intimate relationships -- Acts (and apps) of imagination among today's youth -- Conclusion. Beyond the app generation.

Sommario/riassunto

No one has failed to notice that the current generation of youth is deeply-some would say totally-involved with digital media. Professors Howard Gardner and Katie Davis name today's young people The App Generation, and in this spellbinding book they explore what it means to be "app-dependent" versus "app-enabled" and how life for this generation differs from life before the digital era. Gardner and Davis are concerned with three vital areas of adolescent life: identity, intimacy, and imagination. Through innovative research, including interviews of young people, focus groups of those who work with them, and a unique comparison of youthful artistic productions before and after the digital revolution, the authors uncover the drawbacks of apps: they may foreclose a sense of identity, encourage superficial relations



with others, and stunt creative imagination. On the other hand, the benefits of apps are equally striking: they can promote a strong sense of identity, allow deep relationships, and stimulate creativity. The challenge is to venture beyond the ways that apps are designed to be used, Gardner and Davis conclude, and they suggest how the power of apps can be a springboard to greater creativity and higher aspirations.

2.

Record Nr.

UNINA9910627260103321

Titolo

Artificial Intelligence and Machine Learning for Healthcare : Vol. 1: Image and Data Analytics / / edited by Chee-Peng Lim, Ashlesha Vaidya, Yen-Wei Chen, Tejasvi Jain, Lakhmi C. Jain

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023

ISBN

3-031-11154-0

Edizione

[1st ed. 2023.]

Descrizione fisica

1 online resource (239 pages)

Collana

Intelligent Systems Reference Library, , 1868-4408 ; ; 228

Disciplina

060

610.28563

Soggetti

Computational intelligence

Biomedical engineering

Artificial intelligence

Medical informatics

Computational Intelligence

Biomedical Engineering and Bioengineering

Artificial Intelligence

Health Informatics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

An Introduction to Artificial Intelligence in Healthcare -- Radiomics: Approach to Precision Medicine -- Artificial Intelligence Based Strategies for Data-Driven Radial MRI. .

Sommario/riassunto

Artificial intelligence (AI) and machine learning (ML) have transformed many standard and conventional methods in undertaking health and



well-being issues of humans. AL/ML-based systems and tools play a critical role in this digital and big data era to address a variety of medical and healthcare problems, improving treatments and quality of care for patients. This edition on AI and ML for healthcare consists of two volumes. The first presents selected AI and ML studies on medical imaging and healthcare data analytics, while the second unveils emerging methodologies and trends in AI and ML for delivering better medical treatments and healthcare services in the future. In this first volume, progresses in AI and ML technologies for medical image, video, and signal processing as well as health information and data analytics are presented. These selected studies offer readers theoretical and practical knowledge and ideas pertaining to recent advances in AI and ML for effective and efficient image and data analytics, leading to state-of-the-art AI and ML technologies for advancing the healthcare sector.