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Author: K. Gal
Publisher: IOS Press
ISBN: 164368437X
Category : Computers
Languages : en
Pages : 3328
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Book Description
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
Author: K. Gal
Publisher: IOS Press
ISBN: 164368437X
Category : Computers
Languages : en
Pages : 3328
Get Book Here
Book Description
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.
Author: Triwiyanto Triwiyanto
Publisher: Springer Nature
ISBN: 981971463X
Category :
Languages : en
Pages : 690
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Book Description
Author: Pandey, Binay Kumar
Publisher: IGI Global
ISBN: 1668486202
Category : Computers
Languages : en
Pages : 594
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Book Description
Image processing integrates and extracts data from photos for a variety of uses. Applications for image processing are useful in many different disciplines. A few examples include remote sensing, space applications, industrial applications, medical imaging, and military applications. Imaging systems come in many different varieties, including those used for chemical, optical, thermal, medicinal, and molecular imaging. To extract the accurate picture values, scanning methods and statistical analysis must be used for image analysis. Thrust Technologies Effect on Image Processing provides insights into image processing and the technologies that can be used to enhance additional information within an image. The book is also a useful resource for researchers to grow their interest and understanding in the burgeoning fields of image processing. Covering key topics such as image augmentation, artificial intelligence, and cloud computing, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.
Author: Yashwant Singh
Publisher: Springer Nature
ISBN: 9819906016
Category : Technology & Engineering
Languages : en
Pages : 879
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Book Description
This book features selected papers presented at the 5th International Conference on Recent Innovations in Computing (ICRIC 2022), held on August 13–14, 2022, organized by the ELTE, Hungary in association with Knowledge University, Erbil and many academic and industry partners which includes; European Institute of Data Analytics (EiDA), Dublin, Ireland and CSRL Lab, India . The book is second part of the two volumes, and it includes the latest research in the areas of software engineering, cloud computing, computer networks and Internet technologies, artificial intelligence, information security, database and distributed computing, and digital India.
Author: Biao Luo
Publisher: Springer Nature
ISBN: 9819980674
Category : Computers
Languages : en
Pages : 632
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Book Description
The six-volume set LNCS 14447 until 14452 constitutes the refereed proceedings of the 30th International Conference on Neural Information Processing, ICONIP 2023, held in Changsha, China, in November 2023. The 652 papers presented in the proceedings set were carefully reviewed and selected from 1274 submissions. They focus on theory and algorithms, cognitive neurosciences; human centred computing; applications in neuroscience, neural networks, deep learning, and related fields.
Author: S. N. Kumar
Publisher: CRC Press
ISBN: 1000916243
Category : Computers
Languages : en
Pages : 283
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Book Description
This book explores the role of artificial Intelligence in Telemedicine. It explains the concepts through the detailed study and processing of biosignals, physiological parameters, and medical images. The book focuses on computational algorithms in telemedicine for the processing of biosignals, physiological parameters, and medical Images. The book is presented in two section. The first section presents the role of computational algorithms in the processing of biosignal and medical images for disease diagnosis and treatment planning. Noise removal in ECG signal using an improved adaptive learning approach, classification of ECG signals using CNN for cardiac arrhythmia detection, EEG signal analysis for stroke detection, and EMG signal analysis for gesture classification were discussed in this section. Application of CNN in pertussis Diagnosis by temperature monitoring, physician handwriting recognition using deep learning model, melanoma detection using ABCD parameters, and transfer learning enabled heuristic approach for pneumonia detection was also discussed in this section The second section focus on the role of IoT and artificial intelligence in the healthcare sector. IoT in smart health care and applications of artificial intelligence in disease diagnosis and prediction was discussed in this section. The importance of 5G/6G in the pandemic scenario for telemedicine applications, wireless capsule endoscopy image compression, leukemia detection from the microscopic cell images, and genomic signal processing using numerical mapping techniques was also discussed in this section. This book can be used by a wide range of users including students, research scholars, faculty, and practitioners in the field of engineering for applications in biomedical signal, image analysis, and diagnosis.
Author: Samuel Schäfer
Publisher: Linköping University Electronic Press
ISBN: 9180757081
Category :
Languages : en
Pages : 207
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Book Description
Modern healthcare faces a significant challenge, namely that 25-70% of patients with common diseases do not benefit from standard treatments despite the availability of over 13,000 drugs registered in DrugBank. This discrepancy is likely due to these diseases' complex and heterogeneous molecular nature rather than a lack of therapeutic options. Emerging technologies have revealed the immense molecular complexity underlying common diseases. For instance, singlecell RNA sequencing (scRNA-seq) has demonstrated altered gene interactions in and across multiple cell types in numerous tissues. Furthermore, these technologies have revealed vast molecular differences between patients with the same diagnosis. There is a wide gap between this complexity and the current diagnostic and therapeutic approaches. Aim: To bring personalized medicine one step closer to the clinic; this thesis focuses on developing digital disease models that can capture the molecular biological complexity of disease in individual patients. We aim to harness these disease models to identify optimal treatments for each individual patient. Paper I: We started by exploring the usefulness of OMIC-based approaches for diagnostic and therapeutic predictions. Utilizing a single-cell RNA-sequenced mouse model of antigen-induced arthritis, we aimed to prioritize cell types and therapeutic targets. Initial pathway enrichment analyses did not yield relevant prioritization, prompting an investigation into network-based approaches. Multi-cellular disease models (MCDMs) for AIA and human rheumatoid arthritis were constructed, incorporating predicted cell type interactions. Centrality analysis indicated that these interactions could quantify a cell type’s relative importance in disease pathogenesis. We hypothesized that transcriptomic alterations in central cell types might reflect the MCDM, serving as potential diagnostic markers. An analysis of CD4+ T cells from patients with 13 different inflammatory diseases and healthy controls demonstrated that these profiles could discriminate between healthy and diseased states and among diseases. Furthermore, a network-based approach identified drugs targeting disease- associated changes common to multiple inflammatory diseases. Notably, one of these drugs, bezafibrate, successfully dampened inflammation in the AIA mouse model. Paper II: Building on the insights from Paper I, we investigated multicellular network models (MNMs) with time as an additional dimension. Using seasonal allergic rhinitis (SAR) as a disease model, we analyzed time-series scRNAseq data to construct MNMs of inflammatory diseases. We identified thousands of disease-associated expression changes across multiple cell types, varying at different disease stages. Notably, upstream regulators (URs) of these changes were also stage-dependent and multidirectional. To prioritize URs for drug discovery, we focused on those causing significant expression changes in multiple cell types across all time points. This strategy was validated through similar analyses of atopic dermatitis, ulcerative colitis, and Crohn’s disease, confirming that ranked URs aligned with the efficacy of existing drugs targeting the URs in the respective diseases. Furthermore, experimental validation included targeting the top-ranked regulatory gene in SAR, which was more effective than previously discovered IL4 inhibition. Paper III: While Paper I established the use of transcriptomic data for therapeutic predictions, it focused on overlapping disease-related changes across multiple inflammatory diseases and considered transcriptomic changes in only one cell type. Paper II indicated a potential benefit in UR prioritization in numerous cell types. However, it yielded heterogeneous results and was limited by the fact that few drugs directly target URs. Neither of these approaches was feasible for individualized drug predictions. Drawing on previous insights by us and others, we next aimed to develop digital disease models for individual patients, termed digital twins, with the capability for drug efficacy screening. We proposed scDrugPrio, a strategy utilizing single-cell scRNA-sequencing-based multicellular disease models incorporating key biological and pharmacological properties, such as varying gene expression levels, varying gene interactions within and between cell types, and drug effect. scDrugPrio was constructed based on a mouse model of arthritis and validated by improved precision/recall for known drugs and in vitro studies of predicted drugs that were FDA approved for other diseases and had not yet been tried in rheumatoid arthritis or mouse arthritis. For validation, scDrugPrio was applied to human multiple sclerosis as well as Crohn’s disease data that included tissue samples from healthy and sick tissue of all patients; scDrugPrio was able to identify relevant treatments for individual patients and could distinguish anti-TNF responders from non-responders. Conclusion: This thesis demonstrates a framework for constructing digital disease models for personalized therapeutic predictions that might hold potential for better clinical treatment decisions. By leveraging advanced genome-wide analyses and network-based approaches, we may enhance the precision and efficacy of treatments for immune-mediated inflammatory diseases, bringing personalized medicine closer to clinical reality.
Author: Vijayalakshmi Atluri
Publisher: Springer Nature
ISBN: 3031375866
Category : Computers
Languages : en
Pages : 415
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Book Description
This volume LNCS 13942 constitutes the refereed proceedings of the 37th Annual IFIP WG 11.3 Conference, DBSec 2023, in Sophia-Antipolis, France, July 19–21, 2023. The 19 full papers presented together with 5 short papers were carefully reviewed and selected from 56 submissions. The conference focuses on secure data sharing; access control and vulnerability assessment; machine learning; and mobile applications.
Author:
Publisher: BoD – Books on Demand
ISBN: 183769026X
Category :
Languages : en
Pages : 170
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Book Description
Author: Hawamdeh, Mahmoud M. Kh.
Publisher: IGI Global
ISBN:
Category : Education
Languages : en
Pages : 391
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Book Description
Throughout the educational industry the need to comprehend and navigate the profound transformations underway in the realm of continuing education remains a pressing challenge. As technological advancements accelerate at an unprecedented pace, traditional educational systems are being upended, leaving educators grappling with many questions. The emergence of digital technologies in education introduces a host of complex issues and opportunities. One such opportunity is the application of technologies that can address important issues and open new horizons for those that teach. > At the forefront of academic exploration and innovation is Embracing Technological Advancements for Lifelong Learning, a book of robust research covering an era where the digital revolution is reshaping education. This book brings insights into in-depth investigations of how digital technologies are transforming the landscape of continuing education. It delves deep into the strategies, resources, and best practices that organizations can harness to unlock the full potential of digital transformation. Covering a wide spectrum of issues, from e-learning platforms to virtual and augmented reality, artificial intelligence to mobile learning, this book is a comprehensive guide that showcases the real-world impact of digital transformation through compelling case studies and actionable ideas.
