User Requirements Research Articles

Development of an intelligent platform for predicting curriculum management in higher education under the AUN-QA framework

This research aims to study and define the user requirements and operational capabilities required to develop an intelligent platform for forecasting and managing higher education courses under the AUN-QA framework using documentary research, platform design, and technology suitability assessment. The samples studied include personnel, instructors, course administrators, and IT specialists selected by the purposive method. Data were analyzed using statistics and standard deviation calculations. The results show that the developed platform should have five main components: user data control with AWS IAM and React, access security, SmartEduQA system for data storage and analysis, data presentation with Microsoft Power BI, and a serverless storage system. The platform is designed to meet the needs of administrators in forecasting the labor market and managing courses, instructors in analyzing data according to AUN-QA standards, and staff in managing data quickly and supporting interactive display. This platform can help make higher education course management efficient and aligned with AUN-QA standards.

Addressing the "Black Hole" of Low Back Pain Care With Clinical Decision Support: User-Centered Design and Initial Usability Study.

Low back pain (LBP) is a highly prevalent problem causing substantial personal and societal burden. Although there are specific types of LBP, each with evidence-based treatment recommendations, most patients receive a nonspecific diagnosis that does not facilitate evidence-based and individualized care. We designed, developed, and initially tested the usability of a LBP diagnosis and treatment decision support tool based on the available evidence for use by clinicians who treat LBP, with an initial focus on chiropractic care. Our 3-step user-centered design approach consisted of identifying clinical requirements through the analysis of evidence reviews, iteratively identifying task-based user requirements and developing a working web-based prototype, and evaluating usability through scenario-based interviews and the System Usability Scale. The 5 participating users had an average of 18.5 years of practicing chiropractic medicine. Clinical requirements included 44 patient interview and examination items. Of these, 13 interview items were enabled for all patients and 13 were enabled conditional on other input items. One examination item was enabled for all patients and 16 were enabled conditional on other items. One item was a synthesis of interview and examination items. These items provided evidence of 12 possible working diagnoses of which 3 were macrodiagnoses and 9 were microdiagnoses. Each diagnosis had relevant treatment recommendations and corresponding patient educational materials. User requirements focused on tasks related to inputting data, and reviewing and selecting working diagnoses, treatments, and patient education. User input led to key refinements in the design, such as organizing the input questions by microdiagnosis, adding a patient summary screen that persists during data input and when reviewing output, adding more information buttons and graphics to input questions, and providing traceability by highlighting the input items used by the clinical logic to suggest a working diagnosis. Users believed that it would be important to have the tool accessible from within an electronic health record for adoption within their workflows. The System Usability Scale score for the prototype was 84.75 (range: 67.5-95), considered as the top 10th percentile. Users believed that the tool was easy to use although it would require training and practice on the clinical content to use it effectively. With such training and practice, users believed that it would improve care and shed light on the "black hole" of LBP diagnosis and treatment. Our systematic process of defining clinical requirements and eliciting user requirements to inform a clinician-facing decision support tool produced a prototype application that was viewed positively and with enthusiasm by clinical users. With further planned development, this tool has the potential to guide clinical evaluation, inform more specific diagnosis, and encourage patient education and individualized treatment planning for patients with LBP through the application of evidence at the point of care.

MAD-Onto: an ontology design for mobile app development

IntroductionMobile app development has rapidly evolved into a crucial aspect of modern technology, driving innovation across various industries and transforming user experiences globally. The dynamic nature of mobile technology requires developers to navigate a complex landscape of platforms, devices, and user requirements. Effective management and sharing of knowledge are essential to address these challenges, ensuring streamlined development processes and enhanced collaboration among stakeholders.MethodsTo this end, ontologies have emerged as powerful tools for structuring and standardizing domain-specific knowledge. This paper introduces MAD-onto, a comprehensive ontology designed specifically for the mobile app development domain. The ontology is constructed by identifying key concepts, defining classes and their hierarchies, establishing class properties, and creating instances relevant to mobile app development. To ensure robustness, the ontology is evaluated using a multi-criteria evaluation metric, focusing on consistency, completeness, conciseness, expandability, and sensitiveness. Additionally, SWRL rules are applied to validate and enforce logical constraints within the ontology.ResultsThrough these rigorous evaluation methods, MAD-onto demonstrates its utility in providing a structured framework for the mobile app development lifecycle, facilitating better decision-making, collaboration, and efficiency.DiscussionThe findings highlight the significance of ontology-driven approaches in addressing the complexities of mobile app development and set a foundation for future research and advancements in this field.

Use of SAM in Developing Instructional Numeracy Materials

In the Philippines, numeracy abilities are important because they play a major role in the country’s economic development, technological advancement, and general societal advancement. This study assessed the numeracy skills and proficiency of Grade 6 students of Agaton C. Rodriguez Elementary School. Based on the Albay Numeracy Assessment Tool (ALNAT) pre-test result, the researchers were able to construct instructional videos in Mathematics 6 following the SAM model of instruction, which can help in the improvement of the students who fall in need of major support level during the numeracy assessment. The Mathematics 6 teacher and school ICT coordinator of the selected school served as the validators of the instructional videos and revisions were done according to their comments and recommendations. This study concludes that the SAM proves to be an effective and adaptable approach for designing and developing instructional content. The model promotes a user-centered process that prioritizes continuous refinement by focusing on its three core phases—Preparation, Iterative Design, and Iterative Development. The study also recommends that Instructional designers be open to revisiting earlier phases based on ongoing feedback, ensuring that the final product is continuously refined and meets learners’ evolving needs. Engaged groups during the preparation and development phases help ensure the instructional content remains relevant and user-centered. Further recommends allocating adequate time for the iterative design and development process. For SAM to be successfully implemented, instructional designers should receive proper training on its principles and best practices. Additionally, fostering collaboration between design teams, subject matter experts, and developers is essential for creating high-quality educational resources. Finally, regular evaluation during each phase of the SAM process ensures that instructional content meets both pedagogical and user requirements. Continuous assessment helps identify potential issues early on, leading to more effective solutions before final implementation.

Evaluation of the Digital Ventilated Cage® system for circadian phenotyping

The study of circadian rhythms has been critically dependent upon analysing mouse home cage activity, typically employing wheel running activity under different lighting conditions. Here we assess a novel method, the Digital Ventilated Cage (DVC®, Tecniplast SpA, Italy), for circadian phenotyping. Based upon capacitive sensors mounted under black individually ventilated cages with inbuilt LED lighting, each cage becomes an independent light-controlled chamber. Home cage activity in C57BL/6J mice was recorded under a range of lighting conditions, along with circadian clock-deficient cryptochrome-deficient mice (Cry1−/−, Cry2−/− double knockout). C57BL/6J mice exhibited a 24 h period under light/dark conditions, with a free-running period of 23.5 h under constant dark, and period lengthening under constant light. Animals displayed expected phase shifting responses to jet-lag and nocturnal light pulses. Sex differences in circadian parameters and phase shifting responses were also observed. Cryptochrome-deficient mice showed subtle changes in activity under light/dark conditions and were arrhythmic under constant dark, as expected. Our results show the suitability of the DVC system for circadian behavioural screens, accurately detecting circadian period, circadian disruption, phase shifts and mice with clock defects. We provide an evaluation of the strengths and limitations of this method, highlighting how the use of the DVC for studying circadian rhythms depends upon the research requirements of the end user.

Use of Semantic Web Technologies to Enhance the Integration and Interoperability of Environmental Geospatial Data: A Framework Based on Ontology-Based Data Access

Abstract: This study addresses the challenges of integrating heterogeneous environmental geospatial data by proposing a framework based on ontology-based data access (OBDA). Geospatial data are important for decision-making in various domains, such as environmental monitoring, disaster management, and urban development. Data integration is a common challenge within these domains due to data heterogeneity and semantic discrepancies. The proposed framework uses semantic web technologies to enhance data interoperability, accessibility, and usability. Several practical examples were demonstrated to validate its effectiveness. These examples were based in Lake Mjøsa, Norway, addressing both spatial and non-spatial scenarios to test the framework’s potential. By extending the GeoSPARQL ontology, the framework supports SPARQL queries to retrieve information based on user requirements. A web-based SPARQL Query Interface (SQI) was developed to execute queries and display the retrieved data in tabular and visual format. Utilizing free and open-source software (FOSS), the framework is easily replicable for stakeholders and researchers. Despite some limitations, the study concludes that the framework is able to enhance cross-domain data integration and semantic querying in various informed decision-making scenarios.

Developing a Desktop Voice Assistant

The project aims to develop a personal-assistant for Laptops. Krishna draws its inspiration from virtual assistants like Cortana for Windows, and Siri for iOS but Cortana extends its services to some extent. Our project has been designed to provide a userfriendly interface for carrying out a variety of tasks by employing certain well-defined activities which made it easier to send emails without typing any word, searching on Google without opening the browser, and performing many other daily tasks like playing music, opening your favorite IDE with the help of a single voice command. Users can interact with the assistant either through voice commands or using keyboard inputs. Python is an emerging language so it becomes easy to write a script for Voice Assistant in Python. The instructions for the assistant can be handled as per the requirement of user. In Python there is an API called Speech Recognition which allows us to convert speech into text. It was an interesting task to make our own assistant. By making this project, we realized that the concept of AI in every field is decreasing human effort and saving time. Key Words: NLP(natural language processing),Speech to text conversion

Agile Construction Digital Twin Engineering

Digital twins have attracted a lot of attention recently. However, the current manifestations are merely digital shadows, lacking means for bidirectional data exchange, which makes their use for assisting the construction of buildings much more difficult. We argue that this is due to the lack of a systematic process for developing a digital twin during a building’s life cycle. We argue to look for a solution by combining agile engineering with IT change management to establish an agile, change-driven process for engineering digital twins. Such a process, of course, deserves a qualitative assessment of the engineering process and the resulting digital twin. In the future, it should be possible to obtain a digital twin from a BIM-based design process by applying IT change management in an agile manner. This should happen under maximum automation and life cycle orientation. Our proposal is motivated by several years of interdisciplinary collaboration between civil engineering and computer science and evaluated using the Technology Acceptance Model. While the TAM is not specifically designed for digital twin methodologies, its application here aims to assess perceived usefulness and ease of use of DT methodologies from the user’s perspective, without addressing scalability concerns. This aims to provide actionable insights to guide the refinement of the process model, aligning it with user requirements and achieving its intended outcomes. Our evaluation confirms the proposed process’s perceived usefulness and ease of use, with robust correlations indicating strong acceptance potential among stakeholders. These results highlight the feasibility of the proposed approach and its alignment with expectations in real-world applications.

Readiness for Adopting Artificial Intelligence and Emerging Technologies in Academic Libraries of Pakistan

The integration of artificial intelligence (AI) and emerging technologies is transforming the role and functionality of academic libraries worldwide. The new technological solutions provide academic libraries with superior services and expanded access along with resource utilization enhancements. The successful implementation of these technologies depends on organizations which meet both infrastructure requirements and funding needs and have trained staff while maintaining organizational support. One hundred ninety-nine academic library professionals including librarians and assistant librarians and managers took part in our structured survey that investigated AI application in Pakistan's academic libraries. A Likert-scale questionnaire was used to evaluate knowledge levels and measure institutional readiness as well as training opportunities and perceived challenges. The data evaluation relied on descriptive statistics while SPSS performed the analysis which generated results presented in tables and graphs alongside charts. Research data shows that library professionals demonstrate an average to good command of artificial intelligence knowledge. The adoption of AI faces obstacles because libraries currently struggle with funding problems along with insufficient infrastructure and limited technical capabilities. Most survey participants saw AI's promise for improving library operations yet traditional reluctance alongside ethical uncertainties stood out as vital obstacles to adoption. To solve identified problems training alongside professional advancement programs were established as essential components. The adoption readiness of academic libraries in Pakistan for AI and emerging technologies falls between low and high readiness. The implementation gaps require libraries to invest in structural development along with extensive skill building courses and written policies for the responsible use of AI tools. Organizations must develop strategic plans and increase support for institutions to match worldwide technological developments that meet expanding user requirements.

The Technical Development of a Prototype Lower-Limb Therapy Device for Bed-Resting Users

It is generally recommended that bed-resting patients be mobilised early to promote recovery. The aim of this work was to develop and evaluate the usability of a prototype in-bed lower-limb therapy device that offers various training patterns for the feet and legs, featuring an intuitive user interface and interactive exergames. Based on clinical interviews, the user requirements for the device were determined. The therapy device consisted of two compact foot platforms with integrated electric motors and force sensors. Movement control strategies and a user interface with computer games were developed. Through a touch screen, the target force and position trajectories were defined. Using automatic position and force control algorithms, the device produced leg flexion/extension with synchronised ankle plantarflexion/dorsiflexion as well as leg pressing with adjustable resistive loading. An evaluation test on 12 able-bodied participants showed that the device produced passive (mean position control errors: 8.91 mm linearly and 1.62° in the ankle joints) and active leg training (force control error: 2.52 N). The computer games were proven to be interesting, engaging, and responsive to the training movement. It was demonstrated that the device was technically usable in terms of mechatronics, movement control, user interface, and computer games. The advancements in well-controlled movement, multi-modal training patterns, convenient operation, and intuitive feedback enable the compact therapy device to be a potential system for bed-resting users to improve physical activity and cognitive functionality.

Addressing the Need for a Specialized Disconnection Device in Catheter Connection Management: A Case Study of User-Centered Medical Device Innovation

Background/Objectives: Improvements in catheter connection design intended to increase safety have resulted in connections that are difficult to release manually. No medical device exists to safely disconnect catheter connections. Nurses and other users have developed workarounds including use of hemostats, tourniquets, and wrenches. These workarounds are not always successful for performing this task and can break catheters and catheter connections. This study aimed to evaluate a disconnection device to safely disconnect catheter connections. Methods: This is a mixed-methods study using a user-centered design approach with triangulation of quantitative and qualitative data mapped to Valdez’s sociotechnical framework. Nurses (N = 139) from units across two academic medical centers encompassing diverse patient populations engaged in usability testing and surveys. Data about users’ past catheter disconnection experiences and usability of the specialized disconnection device were collected and analyzed. Triangulation of quantitative data and qualitative themes was mapped using Valdez’s socio-technical framework to complement and strengthen the final design generated for nurses’ user requirements. Results: Ninety-five percent of nurses reported previous difficulty with disconnecting luer connections; 93% of those reporting difficulty improvised with readily available medical devices or products to better grip the connected parts. Over 85% of nurses reported positive experiences using the specialized disconnection device; others suggested design improvements for better performance. Conclusions: The nurses who tested the developed disconnection device reported high acceptability, accessibility, ease of use, and improved task performance. Moreover, as workarounds develop at points of practice where no systematic solution exists, aiming product development activities at these points help close gaps in achieving and maintaining patient safety. This study was not registered.

Research on the ‘Dual-Channel’ design of AR tourism guide digital products on intelligent mobile terminals integrating ‘Digital, Culture, and Tourism’

With the development and popularization of digital technology, AR has become a highly regarded innovative tool in the field of tourism. This study analyzes the current development status of existing digital products for tourist guides, innovatively applying the Analytic Hierarchy Process (AHP), questionnaire surveys, and ‘Dual-Channel’ analysis. Through a more systematic and scientific approach, it identifies top-down and bottom-up user requirements and expectations for AR tourism guide digital product design. The study proposes a series of design strategies based on interface design, interaction design, content provision, and guided tour experience. It quantifies user experience and applies these findings to practical design focused on the Xi’an Tang Dynasty Ever-Bright City. The satisfaction levels across various aspects of the product meet expectations, validating the reliability of the analysis results. This design research provides insights for developing more attractive and practical AR tourism guide digital products.

Traffic and Scenario Adaptive OFDM-IM for Vehicular Networks: A Fuzzy Logic Based Optimization Approach

Orthogonal Frequency Division Multiplexing with Index Modulation (OFDM-IM) holds significant importance in vehicle-to-everything (V2X) communications, with its main advantages being outstanding spectral efficiency and strong interference resistance. However, the existing OFDM-IM systems in vehicular networks overlook actual vehicular network channels and the impact of scatterers, thus failing to accurately reflect the system performance. Moreover, these systems focus solely on the bit error rate (BER) and ignore user requirements for low energy consumption and high spectral efficiency. To address these issues, we propose a user demand- and scenario-adaptive OFDM-IM method that optimizes the OFDM-IM index parameter by considering the spectral efficiency, BER, and energy consumption. Firstly, considering non-line-of-sight components and roadside reflectors, we establish a vehicle-to-vehicle (V2V) communication channel model for straight road scenarios. Then, we construct a transmission framework for vehicular network communication using OFDM-IM. Specifically, we develop an energy efficiency maximization formula, in which fuzzy logic is used to adjust the weights of the three performance indicators to meet various environmental and user requirements. In detail, we discuss the minimum signal-to-noise ratio (SNR) required for OFDM-IM to achieve a lower BER than traditional OFDM in various vehicular communication scenarios. Thus, we can make appropriate choices based on the robustness of the simulation results. The simulation results presented in this paper indicate our method’s effectiveness in enhancing the system’s reliability, efficiency, and flexibility.

Empowering Agile-Based Generative Software Development through Human-AI Teamwork

In software development, the raw requirements proposed by users are frequently incomplete, which impedes the complete implementation of software functionalities. With the emergence of large language models, the exploration of generating software through user requirements has attracted attention. Recent methods with the top-down waterfall model employ a questioning approach for requirement completion, attempting to explore further user requirements. However, users, constrained by their domain knowledge, result in a lack of effective acceptance criteria during the requirement completion, failing to fully capture the implicit needs of the user. Moreover, the cumulative errors of the waterfall model can lead to discrepancies between the generated code and user requirements. The Agile methodologies reduce cumulative errors of the waterfall model through lightweight iteration and collaboration with users, but the challenge lies in ensuring semantic consistency between user requirements and the code generated by the agent. To address these challenges, we propose AgileGen, an agile-based generative software development through human-AI teamwork. Unlike existing questioning agents, AgileGen adopts a novel collaborative approach that breaks free from the constraints of domain knowledge by initiating the end-user perspective to complete the acceptance criteria. By introducing the Gherkin language, AgileGen attempts for the first time to use testable requirement descriptions as a bridge for semantic consistency between requirements and code, aiming to ensure that software products meet actual user requirements by defining user scenarios that include acceptance criteria. Additionally, we innovate in the human-AI teamwork model, allowing users to participate in decision-making processes they do well and significantly enhancing the completeness of software functionality. To ensure semantic consistency between requirements and generated code, we derive consistency factors from Gherkin to drive the subsequent software code generation. Finally, to improve the reliability of user scenarios, we also introduce a memory pool mechanism, collecting user decision-making scenarios and recommending them to new users with similar requirements. AgileGen, as a user-friendly interactive system, significantly outperformed existing best methods by 16.4% and garnered higher user satisfaction.

Radio-sensitivity of selected namibian landrace groundnut (Arachis hypogaea L.) genotypes to gamma radiation.

Groundnut (Arachis hypogaea L.) is a popular nutritious food crop in the world. In Namibia, groundnut varieties are limited and characterized by low yields of 0.4t/ha. Its production is challenged by biotic and abiotic stresses and low genetic variability in the agroecological zones of Namibia. Gamma-irradiation mutagenesis is a technique applied to generate genetic variation based on the genotype's sensitivity to the mutagenic agent for the selection of traits of economic importance that fulfill the user's requirements. This study aimed to determine the optimal lethal doses (LD50) of mutagens producing maximum mutations with minimum damage for mass gamma-irradiation on Namibian landraces of groundnut in preparation for mutation breeding programs. Seeds of three groundnut varieties ('NAM 4433', 'NAM 888/2', 'NAM 1747/1') were subjected to six gamma radiation doses [0, 50, 75, 100, 125, and 150Gy (Gy)]. The radiation source was Cobalt-60, with an irradiation rate of 28.81Gy/min. Irradiated and non-irradiated (control) seeds were sown in plastic pots, using a factorial experiment with a randomized complete block design. Data were collected on parameters relating to seed germination, seedling growth, and plant survival of the varieties. A linear regression model was developed to determine the mean lethal dose (LD50) and reduction dose (RD50) of the varieties. Combined analysis of variance showed significant responses (p<0.001) to seedling emergence, shoot, and root traits. Genotype NAM 4433 was most sensitive to gamma radiation doses ranging from 106 to 150Gy. The doses could be used in mutation breeding programs to select mutants with desirable agronomic and nutritional traits for farmers and consumers. Genotypes NAM 1747/1 and NAM 888/2 did not respond to the doses applied. Further research using high radiation doses for NAM 1747/1 and NAM 888/2 is recommended.

Departing from standard practices: Strategic application of value engineering in the anatomy laboratory to enhance formaldehyde extraction using high-impact, low-cost, and low-maintenance solutions.

This study describes the process of developing a high-impact, low-cost, and low-maintenance air ventilation system for anatomy facilities. It employed the strategic application of Value Engineering (VE), assuring that the air ventilation system meets contemporary threshold limit values (TLVs) for formaldehyde in the working zone of dissection tables. A creative-innovative construction methodology was used, combining the Theory of Inventive Problem Solving (TRIZ/TIPS) and VE for an anatomy laboratory air ventilation concept. The TRIZ/TIPS aimed to resolve conflicts that impeded progress toward higher ideality, while VE aimed to develop alternative approaches to fulfill required functions at a minimal cost. The findings were first trialed in a mockup while dissecting human tissues embalmed with two protocols. The experimental results were validated by computational fluid dynamics simulations, and then followed by a pilot and commissioning phase once the physical installation of the dissection laboratory concluded. The findings demonstrate the superiority of the combined TRIZ/TIPS and VE approach in terms of air distribution and efficient formaldehyde extraction within the breathing zone. A formaldehyde exposition below 0.1 ppm, lowered air exchange rates, and system usability proved that the given third-generation ventilation system complies with contemporary TLVs and potential changes in user requirements. The third-generation ventilation system offers a cost-effective, high-impact, and low-maintenance solution for state-of-the-art air ventilation systems in the anatomy dissection laboratory. The underlying design approach ensured that formaldehyde levels in the laboratory meet the TLV and indoor air guideline values for formaldehyde exposure, at which current knowledge indicates no increased risk of cancer.

Utilizing Serious Games as an Interactive Platform for Programming Learning in Informatics Students

Programming is a critical skill for informatics students, enabling them to design systems, develop software, and analyze user requirements. However, many students face significant challenges in understanding programming concepts and syntax, particularly during the initial stages of learning. These difficulties often stem from limited proficiency in reading, debugging, and writing code, coupled with low motivation and engagement in the learning process. To address these challenges, it is essential to adopt engaging and enjoyable instructional approaches. Serious games have proven to be an effective instructional method, enhancing students' motivation and engagement through game-based elements. This study introduces DolananCoding, a serious game developed as an interactive platform for teaching structured programming courses. DolananCoding incorporates two key features: live coding and a leaderboard, both designed to boost students' motivation and engagement in programming learning. The platform was rigorously evaluated through two testing methods: system testing and user testing. System testing validated the fulfillment of functional requirements, including modules, materials, and experience points, all of which met the expected standards. User testing assessed the platform's user satisfaction through a questionnaire administered to 76 students, yielding an average satisfaction score of 4.3 out of 5.0. These results indicate a positive reception among students, demonstrating the platform's readiness for integration into programming learning.

LIBRARIES OF UKRAINE IN THE CONTEXT OF THE RUSSIAN-UKRAINIAN WAR: NEW CHALLENGES AND DIRECTIONS OF ACTIVITY

The article is devoted to the activities of Ukrainian libraries in the context of the Russian-Ukrainian war. The challenges faced by library institutions are highlighted: physical damage to the infrastructure, relocation of library collections and evacuation of librarians, lack of funding and resources, changes in user requirements, information warfare, emotional burnout of library staff, and technical problems. The author outlines the areas of activity of libraries in times of war, which include information assistance to internally displaced persons, volunteer activities, increasing the digital literacy of the population, educational activities aimed at teaching citizens the skills of first aid, combating disinformation, expanding the provision of digital services, and implementing digital projects. The article reveals the emergence of new functions of libraries, such as the organization of volunteer centers, psychological support, assistance with information security, and the role of libraries as platforms for communication and support of local communities. In times of war, Ukrainian libraries play a key role in supporting the information warfare by actively promoting the dissemination of reliable and verified information among citizens. At a time when information attacks and propaganda by the aggressor are becoming one of the main tools of war, libraries are becoming reliable outposts of truth where people can get information that corresponds to the facts and avoid misinformation.They organize educational events, trainings, and webinars on information literacy, and training in recognizing fake news and manipulation. Through these initiatives, libraries help citizens not only navigate the large flow of information, but also learn to be critical of the sources from which it comes. Such measures contribute to the formation of a culture of safe information consumption in society, which is an important element in the fight against information threats.

Empowering personalized oncology: evolution of digital support and visualization tools for molecular tumor boards

BackgroundMolecular tumor boards (MTBs) play a pivotal role in personalized oncology, leveraging complex data sets to tailor therapy for cancer patients. The integration of digital support and visualization tools is essential in this rapidly evolving field facing fast-growing data and changing clinical processes. This study addresses the gap in understanding the evolution of software and visualization needs within MTBs and evaluates the current state of digital support. Alignment between user requirements and software development is crucial to avoid waste of resources and maintain trust.MethodsIn two consecutive nationwide medical informatics projects in Germany, surveys and expert interviews were conducted as stage 1 (n = 14), stage 2 (n = 30), and stage 3 (n = 9). Surveys, via the SoSci Survey tool, covered participants' roles, working methods, and support needs. The second survey additionally addressed requirements for visualization solutions in molecular tumor boards. These aimed to understand diverse requirements for preparation, implementation, and documentation. Nine semi-structured expert interviews complemented quantitative findings through open discussion.ResultsUsing quantitative and qualitative analyses, we show that existing digital tools may improve therapy recommendations and streamline MTB case preparation, while continuous training and system improvements are needed.ConclusionsOur study contributes to the field by highlighting the importance of developing user-centric, customizable software solutions that can adapt to the fast-paced environment of MTBs to advance personalized oncology. In doing so, it lays the foundation for further advances in personalized medicine in oncology and points to a shift towards more efficient, technology-driven clinical decision-making processes. This research not only enriches our understanding of the integration of digital tools into MTBs, but also signals a broader shift towards technological innovation in healthcare.

Physicians' required competencies in AI-assisted clinical settings: a systematic review.

Utilizing Artificial Intelligence (AI) in clinical settings may offer significant benefits. A roadblock to the responsible implementation of medical AI is the remaining uncertainty regarding requirements for AI users at the bedside. An overview of the academic literature on human requirements for the adequate use of AI in clinical settings is therefore of significant value. A systematic review of the potential implications of medical AI for the required competencies of physicians as mentioned in the academic literature. Our findings emphasize the importance of physicians' critical human skills, alongside the growing demand for technical and digital competencies. Concrete guidance on physicians' required competencies in AI-assisted clinical settings remains ambiguous and requires further clarification and specification. Dissensus remains over whether physicians are adequately equipped to use and monitor AI in clinical settings in terms of competencies, skills and expertise, issues of ownership regarding normative guidance, and training of physicians' skills. Our review offers a basis for subsequent further research and normative analysis on the responsible use of AI in clinical settings. Future research should clearly outline (i) how physicians must be(come) competent in working with AI in clinical settings, (ii) who or what should take ownership of embedding these competencies in a normative and regulatory framework, (iii) investigate conditions for achieving a reasonable amount of trust in AI, and (iv) assess the connection between trust and efficiency in patient care.