Augmented humanity (AH) is a term that has been mentioned in several research papers. However, these papers differ in their definitions of AH. The number of publications dealing with the topic of AH is represented by a growing number of publications that increase over time, being high impact factor scientific contributions. However, this terminology is used without being formally defined. The aim of this paper is to carry out a systematic mapping review of the different existing definitions of AH and its possible application areas. Publications from 2009 to 2020 were searched in Scopus, IEEE and ACM databases, using search terms "augmented human", "human augmentation" and "human 2.0". Of the 16,914 initially obtained publications, a final number of 133 was finally selected. The mapping results show a growing focus on works based on AH, with computer vision being the index term with the highest number of published articles. Other index terms are wearable computing, augmented reality, human-robot interaction, smart devices and mixed reality. In the different domains where AH is present, there are works in computer science, engineering, robotics, automation and control systems and telecommunications. This review demonstrates that it is necessary to formalize the definition of AH and also the areas of work with greater openness to the use of such concept. This is why the following definition is proposed: "Augmented humanity is a human-computer integration technology that proposes to improve capacity and productivity by changing or increasing the normal ranges of human function through the restoration or extension of human physical, intellectual and social capabilities".
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http://dx.doi.org/10.3390/s22020514 | DOI Listing |
Ther Deliv
December 2024
Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research, Hyderabad, India.
Aim: Voriconazole (VRZ) is highly effective in treating invasive pulmonary aspergillosis (IPA), in addition to hepatotoxicity. Therefore, the current study focuses on the development and characterization of voriconazole-loaded microspheres (VRZ@PCL MSPs) to augment pulmonary localization and antifungal efficacy.
Methods: VRZ@PCL MSPs were fabricated by using the o/w emulsion method.
PLoS One
December 2024
Associate Professor of Family Medicine, College of Medicine, King Faisal University, Hofuf, Saudi Arabia.
Background: Continuity of care is a core principle of family medicine associated with improved outcomes. However, fragmentation challenges sustaining continuous relationships. This review aimed to provide timely and critical insights into the benefits of continuity and sustainability of care for older adults.
View Article and Find Full Text PDFArch Dermatol Res
December 2024
Faculty of Medicine, October 6 University, Giza, Egypt.
Background: Various rejuvenation surgeries, including hyaluronic acid (HA) fillers, aim to address mid-face volume loss. However, literature on the comparative efficacy and safety of different HA fillers for the zygomatic area remains limited.
Methods: This systematic review and network meta-analysis (NMA), adhering to NMA PRISMA 2020 and Cochrane guidelines.
Interact J Med Res
December 2024
Department of Respiratory Therapy, College of Applied Medical Sciences, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi Arabia.
Background: Artificial intelligence is experiencing rapid growth, with continual innovation and advancements in the health care field.
Objective: This study aims to evaluate the application of artificial intelligence technologies across various domains of respiratory care.
Methods: We conducted a narrative review to examine the latest advancements in the use of artificial intelligence in the field of respiratory care.
PLoS One
December 2024
Computer and Information Science, Fordham University, New York, New York, United States of America.
Effective communication of government policies to citizens is crucial for transparency and engagement, yet challenges such as accessibility, complexity, and resource constraints obstruct this process. In the digital transformation and Generative AI era, integrating Generative AI and artificial intelligence technologies into public administration has significantly enhanced government governance, promoting dynamic interaction between public authorities and citizens. This paper proposes a system leveraging the Retrieval-Augmented Generation (RAG) technology combined with Large Language Models (LLMs) to improve policy communication.
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