The NCR human interface technology center

BackgroundDespite the unprecedented performance of deep learning algorithms in clinical domains, full reviews of algorithmic predictions by human experts remain mandatory. Under these circumstances, artificial intelligence (AI) models are primarily designed as clinical decision support systems (CDSSs). However, from the perspective of clinical practitioners, the lack of clinical interpretability and user-centered interfaces hinders the adoption of these AI systems in practice.ObjectiveThis study aims to develop an AI-based CDSS for assisting polysomnographic technicians in reviewing AI-predicted sleep staging results. This study proposed and evaluated a CDSS that provides clinically sound explanations for AI predictions in a user-centered manner.MethodsOur study is based on a user-centered design framework for developing explanations in a CDSS that identifies why explanations are needed, what information should be contained in explanations, and how explanations can be provided in the CDSS. We conducted user interviews, user observation sessions, and an iterative design process to identify three key aspects for designing explanations in the CDSS. After constructing the CDSS, the tool was evaluated to investigate how the CDSS explanations helped technicians. We measured the accuracy of sleep staging and interrater reliability with macro-F1 and Cohen κ scores to assess quantitative improvements after our tool was adopted. We assessed qualitative improvements through participant interviews that established how participants perceived and used the tool.ResultsThe user study revealed that technicians desire explanations that are relevant to key electroencephalogram (EEG) patterns for sleep staging when assessing the correctness of AI predictions. Here, technicians wanted explanations that could be used to evaluate whether the AI models properly locate and use these patterns during prediction. On the basis of this, information that is closely related to sleep EEG patterns was formulated for the AI models. In the iterative design phase, we developed a different visualization strategy for each pattern based on how technicians interpreted the EEG recordings with these patterns during their workflows. Our evaluation study on 9 polysomnographic technicians quantitatively and qualitatively investigated the helpfulness of the tool. For technicians with <5 years of work experience, their quantitative sleep staging performance improved significantly from 56.75 to 60.59 with a P value of .05. Qualitatively, participants reported that the information provided effectively supported them, and they could develop notable adoption strategies for the tool.ConclusionsOur findings indicate that formulating clinical explanations for automated predictions using the information in the AI with a user-centered design process is an effective strategy for developing a CDSS for sleep staging.

—Thailand, as well as many other countries worldwide, is facing a shortage of medical staff. We propose a solution to improve medical services in rural areas: a robot teleoperation system that allow patients to consult with doctors from public hospitals, and for doctors to examine and make decisions about their required care. To develop such a system, we are following a user-centred design (UCD) process. Two research questions have been addressed: how should an effective robot teleoperation system be designed to support medical diagnosis and patient communication? And does the use of a social robot improve the social interaction and examination quality in a remote consultation? This paper discusses the overall UCD process, starting from requirement analysis with Thai end-users (finished), system design and development on Pepper robot (in-progress), and user-centred evaluation (future plan).

Scientific data volumes have been growing exponentially. This has resulted in the need for new tools that enable users to operate on and analyze data. Cyber infrastructure tools, including workflow tools, that have been developed in the last few years has often fallen short if user needs and suffered from lack of wider adoption. User-centered Design (UCD) process has been used as an effective approach to develop usable software with high adoption rates. However, UCD has largely been applied for user-interfaces and there has been limited work in applying UCD to application program interfaces and cyber infrastructure tools. We use an adapted version of UCD that we refer to as Scientist-Centered Design (SCD) to engage with users in the design and development of Tigres, a workflow application programming interface. Tigres provides a simple set of programming templates (e.g., sequence, parallel, split, merge) that can be can used to compose and execute computational and data transformation pipelines. In this paper, we describe Tigres and discuss our experiences with the use of UCD for the initial development of Tigres. Our experience-to-date is that the UCD process not only resulted in better requirements gathering but also heavily influenced the architecture design and implementation details. User engagement during the development of tools such as Tigres is critical to ensure usability and increase adoption.

Even though User-Centred Design (UCD) is widely accepted and employed in the design and development of interactive systems, there are limited guiding procedures on how such approaches can be translated to the development of products, systems, and services that are focusing primarily on accessibility. This paper reports on the application of UCD for such a system within an EU project CONTENT4ALL under the domain accessibility for the Deaf. Each step in the UCD process and the respective activities within each step are described in detail with a focus on the methods and techniques adopted for assisting in the development of the novel technology. The insights gained during the entirety of the user-centred design and evaluation process have led to a compilation of important factors for creating sign-translated media content. This possible guideline comprises a list of useful and necessary components pertaining to sign language delivery in media, particularly sign television. The objective of this paper is to highlight lessons learned presented in the form of recommendations for human factors researchers on key UCD procedures for the development of accessibility products, systems and services based on the performed user activities within the project. An attempt has been made to reduce the gap in literature and add to a possible UCD guiding process exclusively for accessibility.

Artificial Intelligence in the American Healthcare Industry: Looking Forward to 2030

Since the emergence of artificial intelligence (AI) in the graphic design field in 2016, it has posed a severe threat to the traditional graphic design industry and designers. In this critical situation, how the traditional graphic design industry will develop in the next step has become the focus of concern in many people, especially practitioners in the graphic design industry. Hence, the future development path of graphic design is analyzed from the perspective of AI in this paper, which mainly includes four aspects as follows: the multi-dimensional performance of graphic design, the integration of new technologies in graphic design, the “interdisciplinary” cultivation of talents, as well as the positioning and promotion of graphic designers. It is expected that the analysis of these four aspects can provide some reference for the future development of the graphic design industry.

The 21st century has embraced many innovations as the year of high technology. With this developing high technology, as the list of things to do on the internet and computers increases, new applications and programs made with artificial intelligence increase. Especially in parallel with the development of computer technology, computers have learned to draw pictures, play games and chat better than humans with the word commands they write to the artificial intelligence bot. There are many applications that have emerged in this sense. Within the framework of these developments, the needs have diversified and this situation is reflected in the professions. Applications produced with artificial intelligence, while reducing the need for some professions, also allowed the creation of new professions. In this sense, it is entirely up to the user experience how the graphic design field, which is seen as one of the professions where the need has decreased, will use and develop artificial intelligence. The use of artificial intelligence and technology in the field of graphic design has been discussed more and more in recent years. At the center of these discussions is the role and impact of artificial intelligence and technology in the graphic design process. On the one hand, the use of artificial intelligence and technology can speed up the design process and enable to work more efficiently, on the other hand, it can cause concerns in terms of creativity and aesthetics of design. In particular, concerns are expressed about the designs produced with artificial intelligence-based design tools and the dependence of the designers on their creativity and the originality of these designs. Within the scope of this research, recent applications were examined regarding search answers for the questions of how can graphic design field, graphic designer and graphic design education be affected in this sense? How does it affect creativity? What can images produced by artificial intelligence with our knowledge based on visual culture teach us?. The findings of the research reveal designers working in the field of graphic design have to constantly renew and update themselves in order to follow the innovations in the field. In addition, they should be careful that the designs they make with the applications they use are not an ethical problem. Therefore, while the use of artificial intelligence and technology in the field of graphic design is expected to increase, more research is needed on the effects of artificial intelligence and technology use in the design process and its usage areas.

Integration of cognitive systems across disciplinary boundaries

This paper involves the review of papers related to an efficient ambulance management system in this project report we will be going through research papers related to similar topics and find information to improve the process of making an ambulance intelligent. India’s population is increasing as each day is passing. The increase in population puts a lot of strain and management of resources from medical, government services and many more. The strain on the resources results in citizens not getting proper help in the time of need. The main example of this process is ambulance management system which is the first line of help process in time of need. If a patient or a victim does not get an ambulance in time then the patient’s life is surely at risk. So there needs to be proper mechanism to handle this important resource and help patients in time. Latest technologies such as cloud computing, IoT, AI, ML and mobile computing can be used to improve the ambulance management and emergency help services. . Ambulance service is one of the crucial services that gets delayed. Sometimes on-sight doctors are not available, so the patient does not get medical attention immediately. In health monitoring system, the patient's vital health parameters such as ECG, Heart Rate and Body Temperature are monitored. These parameters are sent the hospital server using IoT and cloud technology. In the current era of technology, Artificial Intelligence (AI) is playing a vital role in the health care sector especially cardiac disease detection which is a major cause of sudden death. The work given here is a mini-project that is taken up as a part of the curriculum completed by electronics and communication engineering students in the second year of the electronics &amp; communication engineering department at Dayananda Sagar College of Engineering in Bangalore.

BackgroundStressful situations during intraoperative emergencies have negative impact on human cognitive functions. Consequently, task performance may decrease and patient safety may be compromised. Cognitive aids can counteract these effects and support anesthesiologists in their crisis management. The Professional Association of German Anesthesiologists set up a project to develop a comprehensive set of digital cognitive aids for intraoperative emergencies. A parallel development for several software platforms and stationary and mobile devices will accommodate the inhomogeneity of the information technology infrastructure within German anesthesia departments.ObjectiveThis paper aimed to provide a detailed overview of how the task of developing a digital cognitive aid for intraoperative crisis management in anesthesia was addressed that meets user requirements and is highly user-friendly.MethodsA user-centered design (UCD) process was conducted to identify, specify, and supplement the requirements for a digital cognitive aid. The study covered 4 aspects: analysis of the context of use, specification of user requirements, development of design solutions, and evaluation of design solutions. Three prototypes were developed and evaluated by end users of the application. Following each evaluation, the new requirements were prioritized and used for redesign. For the first and third prototype, the System Usability Scale (SUS) score was determined. The second prototype was evaluated with an extensive Web-based questionnaire. The evaluation of the third prototype included a think-aloud protocol.ResultsThe chosen methods enabled a comprehensive collection of requirements and helped to improve the design of the application. The first prototype achieved an average SUS score of 74 (SD 12), indicating good usability. The second prototype included the following main revisions: 2-column layout, initial selection of patient type (infant, adult, or parturient), 4 offered search options, and the option to check off completed action steps. Its evaluation identified the following major revision points: add quick selection for resuscitation checklists, design the top bar and tabs slightly larger, and add more pictograms to the text. The third prototype achieved an average SUS score of 77 (SD 15). The evaluation of the think-aloud protocol revealed a good intuitiveness of the application and identified a missing home button as the main issue.ConclusionsAnesthesiology—as an acute medical field—is particularly characterized by its high demands on decision making and action in dynamic, or time-critical situations. The integration of usability aspects is essential for everyday and emergency suitability. The UCD process allowed us to develop a prototypical digital cognitive aid, exhibiting high usability and user satisfaction in the demanding environment of anesthesiological emergencies. Both aspects are essential to increase the acceptance of the application in later stages. The study approach, combining different methods for determining user requirements, may be useful for other implementation projects in a highly demanding environment.

The rapid advancement of AI technology has led to increasingly complex and opaque systems, creating a critical need for explainable AI (XAI) that enhances transparency and user trust. Despite extensive research on XAI methods and applications, the user-centered design (UCD) process for XAI remains fragmented and unclear. This systematic review analyzes 27 studies from 2020 to 2024 to develop a comprehensive framework for user-centered XAI system design (UCXAISD). We identify five key stages: contextual inquiry, explanation needs identification, XAI method selection, user interface design, and evaluation and refinement. Our framework aligns with traditional UCD processes while incorporating specialized elements for XAI, including user-centricity, transparency, and actionability. For each stage, we provide evidence-based guidelines derived from the literature. The framework serves as a blueprint for developing XAI systems that balance technical sophistication with user needs.

Forest and land fires have become a national issue every year, especially in West Kalimantan. From 2015 to 2020, around 331,268.35 hectares of forest and land were burned in West Kalimantan. As a result of forest and land fires, the haze disrupts public health, the economy, and river, land, sea, and air transportation. As anticipation and prevention, the community and government monitor forest and land fires using the Forest Fire Monitoring System Application. The purpose of this study was to the User Experience (UX) evaluation for design improvement in the Forest Fire Monitoring System Application (SIPONGI) inWest Kalimantan. The method used was User Centered Design (UCD) and Website Usability Evaluation Tool (WEBUSE) to provide new design solutions in the form of a website prototype. The research methodology included a literature study of the SIPONGI application. The study used a sample of 25 respondents with different work backgrounds to represent the population using the SIPONGI application. The results of this study showed that usability points per attribute and category are superior after making UI/UX improvements using the UCD process in prototype form. In conclusion, using the UCD method is better if it is accompanied by the WEBUSE method in improving the design of an application.

The article is devoted to the issues of forming the conceptual bases for the development and application of artificial intelligence technologies in the forecasting of economic processes. The relevance of developing a conceptual approach to the application of artificial intelligence technologies to predicting economic processes is substantiated. An overview analysis of relevant related scientific research works was conducted and the state of problem development was studied. Artificial intelligence includes machine and deep learning, natural language processing, computer vision, expert systems, fuzzy logic, genetic algorithms, etc. such methods and means were explained. Artificial intelligence methods based on evolution-algorithm, Data-mining technology, machine learning technology, and computer vision were analyzed in forecasting economic processes. The basis of the application of the neoclassical production function in predicting the impact of artificial intelligence on economic growth has been investigated. Neoclassical models were used to investigate the impact of artificial intelligence technology on production. Based on data mining technology, the economic development potential forecasting model and its forecasting adequacy were explained. The structural scheme of the main components of the application of artificial intelligence technology in the forecasting of economic processes has been developed. In order to increase the stability of economic development and predict economic processes by means of artificial intelligence technologies, relevant proposals, and recommendations were made, taking into account the technological requirements and priorities of the elements of the Industry 4.0 platform.

The research focus was motivated by the limited understanding of cognitive technologies and the growing gap between artificial intelligence (AI) and human intelligence. The research is a literature review, and its purpose is to simplify the meaning and processes behind cognitive technologies, notably, the fundamentals of machine learning (ML) and computer vision with the intention to briefly address the alleged threat of AI taking over the job market. The research is a review of peer-reviewed articles retrieved from comparative studies, systematic reviews, meta-analysis, service research, reports, conference proceedings, experimental studies, literature reviews, scientometric analyses, books, and multi-case studies, dating from the years of 2018 to 2024. This literature review defines machine learning (ML), artificial intelligence (AI), computer vision, and convolutional neural networks (CNNs). It also compares machine learning to traditional programming and reveals the types of learning in ML models’ training. ML and its correlation with AI are also discussed and details about theory of mind, self-aware AI, reactive machines, and limited memory AI are shared. The literature expounds computer vision, particularly convolutional neural network (CNN) and CNN layers. Recent cutting-edge applications of artificial intelligence including generative AI models and autonomous systems are also incorporated. Finally, the literature briefly addresses the alleged threat of AI taking over the job market. The findings of this literature review reveal that AI is becoming the new way of operating. The conclusion shows that AI models require significant computation to allow computers to learn autonomously. Thus, understanding mathematical models of data and perfecting the process of writing software could be the key to remaining employable as more jobs are expected to be shifted due to AI and tasks automation. Keywords: Cognitive technology, artificial intelligence, machine learning, computer vision, convolutional neural networks

The paper addresses the issue of the holistic assembly of strategic subjects that cannot be carried out by classical approaches with logical and formalized techniques only. To take into consideration non-formalizable aspects of collective decision-making (unconscious, corporate spirit, emotions, feelings, thoughts, meditations, etc.), the principles of ensuring the convergence of the holistic assembly are formulated based on the methods of inverse problem-solving, artificial intelligence, category and topology theories, thermodynamics, and quantum semantics. This paper focuses on the application of quantum semantics that helps to accelerate the convergence of the holistic assembly of strategic subjects, making it more purposeful and sustainable. Some practical applications are listed.