scholarly journals Data Protection in AI Services

2021 ◽  
Vol 54 (2) ◽  
pp. 1-38
Author(s):  
Christian Meurisch ◽  
Max Mühlhäuser
Keyword(s):  
Artificial Intelligence ◽  
Data Protection ◽  
Interdisciplinary Research ◽  
Management System ◽  
Cutting Edge ◽  
Future Directions ◽  
Research Challenges ◽  
Open Research ◽  
User Data ◽  
Different Levels

Advances in artificial intelligence (AI) have shaped today’s user services, enabling enhanced personalization and better support. As such AI-based services inevitably require user data, the resulting privacy implications are de facto the unacceptable face of this technology. In this article, we categorize and survey the cutting-edge research on privacy and data protection in the context of personalized AI services. We further review the different protection approaches at three different levels, namely, the management, system, and AI levels—showing that (i) not all of them meet our identified requirements of evolving AI services and that (ii) many challenges are addressed separately or fragmentarily by different research communities. Finally, we highlight open research challenges and future directions in data protection research, especially that comprehensive protection requires more interdisciplinary research and a combination of approaches at different levels.

scholarly journals Artificial Intelligence in Digital Pathology: What Is the Future? Part 1: From the Digital Slide Onwards

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 858
Author(s):  
Maria Rosaria Giovagnoli ◽  
Daniele Giansanti
Keyword(s):  
Artificial Intelligence ◽  
Digital Pathology ◽  
Point Of View ◽  
Digital Slide ◽  
Future Directions ◽  
Research Perspectives ◽  
Research Challenges ◽  
The Future

This commentary aims to address the field of Artificial intelligence (AI) in Digital Pathology (DP) both in terms of the global situation and research perspectives. It has four polarities. First, it revisits the evolutions of digital pathology with particular care to the two fields of the digital cytology and the digital histology. Second, it illustrates the main fields in the employment of AI in DP. Third, it looks at the future directions of the research challenges from both a clinical and technological point of view. Fourth, it discusses the transversal problems among these challenges and implications and introduces the immediate work to implement.

scholarly journals Artificial Intelligence in dentistry: Concepts, Applications and Research Challenges

2021 ◽  
Vol 297 ◽  
pp. 01074
Author(s):  
Achsha Babu ◽  
J. Andrew Onesimu ◽  
K. Martin Sagayam
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Future Directions ◽  
Human Essence ◽  
Research Challenges ◽  
Different Types ◽  
Precise Diagnosis ◽  
Clinical Practise ◽  
To Come ◽  
Applications Of Ai

Artificial Intelligence (AI) has the ability to process huge datasets, disclose human essence computationally, and perform like humans as technology advances. Because of the necessity for precise diagnosis and improved patient care, AI technology has greatly influenced the healthcare industry. In the domains of dentistry and medicine, artificial intelligence has yet to come a long way. As a result, dentists must be aware of the potential implications for a profitable clinical practise in the future. In this paper, we present the current applications of AI in dentistry. The different types of AI techniques are introduced and summarized. The state-of-the-art literature is studied analysed. A comparative analysis on the different AI techniques in dentistry is presented. Further, the research challenges in the field of dentistry and future directions are also provided.

scholarly journals Bone Age Assessment Empowered with Deep Learning: A Survey, Open Research Challenges and Future Directions

Diagnostics ◽  
2020 ◽  
Vol 10 (10) ◽  
pp. 781
Author(s):  
Muhammad Waqas Nadeem ◽  
Hock Guan Goh ◽  
Abid Ali ◽  
Muzammil Hussain ◽  
Muhammad Adnan Khan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Medical Images ◽  
Bone Age ◽  
Learning Models ◽  
Age Assessment ◽  
Future Directions ◽  
Research Challenges ◽  
Open Research ◽  
Wide Range ◽  
Bone Age Assessment

Deep learning is a quite useful and proliferating technique of machine learning. Various applications, such as medical images analysis, medical images processing, text understanding, and speech recognition, have been using deep learning, and it has been providing rather promising results. Both supervised and unsupervised approaches are being used to extract and learn features as well as for the multi-level representation of pattern recognition and classification. Hence, the way of prediction, recognition, and diagnosis in various domains of healthcare including the abdomen, lung cancer, brain tumor, skeletal bone age assessment, and so on, have been transformed and improved significantly by deep learning. By considering a wide range of deep-learning applications, the main aim of this paper is to present a detailed survey on emerging research of deep-learning models for bone age assessment (e.g., segmentation, prediction, and classification). An enormous number of scientific research publications related to bone age assessment using deep learning are explored, studied, and presented in this survey. Furthermore, the emerging trends of this research domain have been analyzed and discussed. Finally, a critical discussion section on the limitations of deep-learning models has been presented. Open research challenges and future directions in this promising area have been included as well.

scholarly journals Empirical Evaluation of Privacy Efficiency in Blockchain Networks: Review and Open Challenges

2021 ◽  
Vol 11 (15) ◽  
pp. 7013
Author(s):  
Aisha Zahid Junejo ◽  
Manzoor Ahmed Hashmani ◽  
Mehak Maqbool Memon
Keyword(s):  
Empirical Evaluation ◽  
Evaluation Criteria ◽  
Building Blocks ◽  
Evaluation Framework ◽  
Smart Contracts ◽  
Future Directions ◽  
Blockchain Technology ◽  
Research Challenges ◽  
Open Research ◽  
Memory Time

With the widespread of blockchain technology, preserving the anonymity and confidentiality of transactions have become crucial. An enormous portion of blockchain research is dedicated to the design and development of privacy protocols but not much has been achieved for proper assessment of these solutions. To mitigate the gap, we have first comprehensively classified the existing solutions based on blockchain fundamental building blocks (i.e., smart contracts, cryptography, and hashing). Next, we investigated the evaluation criteria used for validating these techniques. The findings depict that the majority of privacy solutions are validated based on computing resources i.e., memory, time, storage, throughput, etc., only, which is not sufficient. Hence, we have additionally identified and presented various other factors that strengthen or weaken blockchain privacy. Based on those factors, we have formulated an evaluation framework to analyze the efficiency of blockchain privacy solutions. Further, we have introduced a concept of privacy precision that is a quantifiable measure to empirically assess privacy efficiency in blockchains. The calculation of privacy precision will be based on the effectiveness and strength of various privacy protecting attributes of a solution and the associated risks. Finally, we conclude the paper with some open research challenges and future directions. Our study can serve as a benchmark for empirical assessment of blockchain privacy.

scholarly journals Some Aspects of Information Security in Digital Organizational Management System

2020 ◽  
pp. 279-289
Author(s):  
Olena Skrynnyk
Keyword(s):  
Artificial Intelligence ◽  
Information Security ◽  
Organizational Development ◽  
Data Protection ◽  
Management System ◽  
Process Analysis ◽  
Personal Data ◽  
Data Access ◽  
Organizational Management ◽  
Digital Systems

Organizational development is one of the most important fields of organizational management. With increasing connectivity and digitalization of processes, systems, and data, intrusions via interfaces and subsystems can be affected by the entire system’s security. The manipulation or loss of data in artificial intelligence-based systems takes on a serious role, as the technology learns and acts based on data. Since personal and person-related data and confidential company data are of particular importance, this issue’s relevance is significant. This study aimed to determine the data access limit for digital systems for organizational development and to investigate user attitudes towards the procession of personal data through artificial intelligence. The main purpose is to provide the research results to target selected security and data protection aspects in the design of organizational development systems based on artificial intelligence. Investigation of this topic is carried out in three logical phases. The first phase provides the analysis of scientific publications. It explores how and under which aspects and conditions digital systems for organizational development depend on information security and data protection. The literature review included keyword network analysis in Scopus with further visualization in VOSviewer. The second part provides a targeted data classification according to security classes, which can be directly applied to design organizational development or management software. In the third phase, there is a survey of respondents from Ukraine and Germany to determine the attitudes towards collecting and analyzing personal data through artificial intelligence. The investigation results show the close connection of the subject’s security and data protection with the change management system, privacy, development of technological models in enterprises, applications for and of process analysis, the legislative basis for information security, etc. According to the survey, the respondents from Ukraine show more neutrality in accepting the collection of personal or personal data through artificial intelligence. Across age and nationality, it can be stated that the majority of respondents are not opposed to collecting and analyzing data about the execution of the activity or behavior, personal details, family status, education. Scientists and practitioners can directly use the findings for further applications in developing digital systems for organizational development. Keywords: information security of organizational development system, artificial intelligence for organizational development, protection of organizational data, protection of personal data.

Artificial intelligence for Novel Corona Virus (COVID-19) Pandemic

2022 ◽  
Vol 13 (2) ◽  
pp. 0-0
Keyword(s):  
Artificial Intelligence ◽  
Language Processing ◽  
Medical Diagnosis ◽  
Economic Sectors ◽  
Future Directions ◽  
Research Challenges ◽  
The World ◽  
Crowd Surveillance ◽  
The Impact

COVID-19 outbreak has created havoc around the world and has brought life to a disturbing halt claiming thousands of lives worldwide and infected cases rising every day. With technological advancements in Artificial Intelligence (AI), AI-based platforms can be used to deal with COVID-19 pandemic and accelerate the processes ranging from crowd surveillance to medical diagnosis. This paper renders a response to battle the virus through various AI techniques by making use of its subsets such as Machine Learning (ML), Deep learning (DL) and Natural Language Processing (NLP). A survey of promising AI methods which could be used in various applications to facilitate the processes in this pandemic along potential of AI and challenges imposed are discussed thoroughly. This paper relies on the findings of the most recent research publications and journals on COVID-19 and suggests numerous relevant strategies. A case study on the impact of COVID-19 in various economic sectors is also discussed. The potential research challenges and future directions are also presented in the paper.

MODERN INFORMATICS: FROM ROBOTICS TO ARTIFICIAL INTELLIGENCE

2018 ◽  
Vol 1 (8) ◽  
pp. 2-5 ◽  
Author(s):  
L. L. Bosova ◽  
N. N. Samylkina
Keyword(s):  
Artificial Intelligence ◽  
Different Levels

The article describes the work of Informatics Club in the framework of the project "Children University of MPSU". It is considered how it is possible to realize the development of complex questions of informatics in the framework of Club work with students of different levels of education.

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