Computer-assisted Language Learning Research Articles

Evaluating the efficacy of Kahoot as a computer-assisted language learning tool in higher education

This study aimed to analyse the effectiveness of using the computer tool Kahoot for foreign language learning in higher education, as well as to address the problem of students' lack of motivation in learning English. This study hypothesised that using the Kahoot app in foreign language classes would improve students' motivation through its engaging approach. To test this hypothesis, a survey was conducted among students who had studied English using this tool. The results showed that students who used the Kahoot app in the classroom were significantly more motivated to learn English. This was made possible by the app's ability to vary the learning tool depending on the needs of the students, which encouraged their active participation in the learning process. The effectiveness of Kahoot as a tool in higher education for learning foreign languages is promising. Its engaging and interactive format, instant feedback, and collaborative learning opportunities make it a valuable tool for enhancing language learning. However, it is important for teachers to be aware of its limitations and complement it with other activities to ensure comprehensive language development. Overall, Kahoot can be a valuable addition to the language learning toolkit in higher education.

Generating Genre-Based Automatic Feedback on English for Research Publication Purposes

Artificial intelligence (AI) for supporting second language (L2) writing processes and practices has garnered increasing interest in recent years, establishing AI-mediated L2 writing as a new norm for many multilingual classrooms. As such, the emergence of AI-mediated technologies has challenged L2 writing instructors and their philosophies regarding computer-assisted language learning (CALL) and teaching. Technologies that can combine principled pedagogical practices and the benefits of AI can help to change the landscape of L2 writing instruction while maintaining the integrity of knowledge production that is so important to CALL instructors. To align L2 instructional practices and CALL technologies, we discuss the development of an AI-mediated L2 writing technology that leverages genre-based instruction (GBI) and large language models to provide L2 writers and instructors with tools to enhance English for research publication purposes. Our work reports on the accuracy, precision, and recall of our network classification, which surpass previously reported research in the field of genre-based automated writing evaluation by offering a faster network training approach with higher accuracy of feedback provision and new beginnings for genre-based learning systems. Implications for tool development and GBI are discussed.

ChatGPT as a CALL tool in language education: A study of hedonic motivation adoption models in English learning environments

AbstractThe advancement of information technologies has led to increased attention to AI chatbots as valuable tools for computer-assisted language learning (CALL), drawing the attention of both academic scholars and industry practitioners. However, there remains limited understanding regarding the adoption of AI chatbots, specifically within the context of the English language. To address this existing research gap and examine the perception and motivation of usage of ChatGPT, this research employed the hedonic motivation system adoption model (HMSAM) to examine the adoption of ChatGPT. Employing structural equation modelling (SEM), a comprehensive investigation was conducted using data sourced from 189 valid responses obtained through an online survey administered to Chinese international students who are currently enrolled in British universities. The findings reveal that the research model effectively elucidates the elements influencing the adoption of ChatGPT in English learning. Notably, boredom, joy, focused immersion, and control emerged as significant mediating factors pertaining to the link between perceived ease of use and behavioural intention. These findings offer meaningful perspectives for upcoming researchers and practitioners in English language teaching and learning, contributing to promoting innovation in this domain.

Assessing Intercultural Communicative Competence in British Council Algeria

Due to globalization and technological advancement, the world has become open and people have unrestricted access to an infinite amount of resources. Computer technology and web-based gadgets are hereby considered imperative for personal, educational, and professional development. Reliance on computer-based instruction has rendered the teaching and the learning processes appealing and rarefied. The result, or the basic outcome, would be individuals able to fit in the ever-changing globalized world and who are able to transcend far beyond content users to content creators. The purpose of this study is to demonstrate what contributions computer assisted language learning (CALL) has on the educational system in general and on students in particular, and how effective teaching and learning can be optimized. Another aim of this research is to recognize how CALL contributes to the behavioral, cognitive, and meta-cognitive development of the learners. British Council is a web-based platform that offers varied instructional contents for learners from across the globe. This paper seeks to show how British Council, as a form of CALL, contributes in developing learners’ communicative competence and intercultural skills.

A craniometric study of the Medieval sample from Deraheib (Northern Sudan)

The history of North Africa has been always tightly connected to events occurring in Eurasia. Human migra-tions in both directions are well-documented in written sources and archaeological records. To gain a comprehen-sive understanding of historical processes, it is essential to study the remains of individuals who inhabited this region during various time periods. A lack of cranial metric data on the Medieval population of North Africa im-pedes thorough investigation of the population history of the region. This paper presents a craniometric study of the sample from the Southern necropolis at Deraheib. This study contributes to filling the existing void in the un-derstanding of the Medieval population of North Africa. According to written sources, the site was a center of gold mining, known as the city of al-Allaki, dated to the 9th to 15th centuries AD. The city attracted a diverse population seeking economic opportunities. Besides this, Al-Allaki served as an important point on the caravan route which was utilized by merchants and pilgrims traversing the Nubian Desert on their way to Jeddah. The study analyzes cranial metrics of a total of 23 individuals (14 male and 9 female) skulls recovered from the southern necropolis Deraheib sample and employs 55 linear dimensions, following Martin's/Howells craniometric protocol as well as some additional measurements. Statistical analyses were performed using the R language packages and the Multican software. Our results revealed heterogeneity of the sample in male and female parts of the sample at the intra-group level: an observation aligning with existing archaeological and historical evidence. The limited size of the sample warns against any firm conclusions regarding affinities of the Deraheib population. Our intergroup comparison has shown that the cranial sample from the Southern Necropolis of the Deraheib site displays morphological features that are more similar to neighboring Caucasoid populations rather than equatorial groups from East Africa.

Network pharmacology and molecular docking studies on the mechanism of action of moist exposed burn ointment for treatment of diabetic foot ulcer

Purpose: To investigate the bioactive components and mechanism of action of moist exposed burn ointment (MEBO) for treatment of diabetic foot ulcers using network pharmacology (NP) and molecular docking technology 
 Methods: Through pharmacology database of traditional Chinese medicine (TCM) systems (TCMSP), analysis platform and symptom mapping (SymMap) database, the bioactive components of MEBO were screened for and protein binding to bioactive components was predicted. Proteins related to Diabetic foot ulcer (DFU) were collected from GeneCards, OMIM, PharmGkb and TTD disease databases. With R language software, the binding proteins of bioactive components of MEBO intersected with the proteins related to occurrence of DFU. Proteins of DFU linked to treatment with MEBO were subjected to analysis using gene ontology (GO) and KEGG with R language software. AutoDock and PyMOL software were employed to dock active components of MEBO and major proteins of DFU. Targeted binding potential of bioactive compounds in MEBO to core proteins of DFU was analyzed. 
 Results: One hundred and five (105) bioactive ingredients and 246 likely therapeutic proteins were obtained. Proteins were mainly involved in biological processes in wound healing, oxidative stress, and lipopolysaccharide. The enriched signaling pathway focused on lipid metabolism and the process of atherosclerosis which involved PI3K and Akt, advanced glycation end-products (AGE)-receptor (RAGE) and mitogen-activated protein kinase (MAPK). The absolute values of these proteins were screened out with a docking score greater than 5 kcal/mol. 
 Conclusion: The biological effects of MEBO are related to multiple proteins and multiple signaling pathways. Therefore, healing effect of MEBO on DFU occurs via multiple pathways. The biological characteristics of MEBO need to be fully elucidated in further studies.

Performance of Two Artificial Intelligence Generative Language Models on the Orthopaedic In-Training Examination.

Artificial intelligence (AI) generative large language models are powerful and increasingly accessible tools with potential applications in health care education and training. The annual Orthopaedic In-Training Examination (OITE) is widely used to assess resident academic progress and preparation for the American Board of Orthopaedic Surgery Part 1 Examination. Open AI's ChatGPT and Google's Bard generative language models were administered the 2022 OITE. Question stems that contained images were input without and then with a text-based description of the imaging findings. ChatGPT answered 69.1% of questions correctly. When provided with text describing accompanying media, this increased to 77.8% correct. In contrast, Bard answered 49.8% of questions correctly. This increased to 58% correct when text describing imaging in question stems was provided (P<.0001). ChatGPT was most accurate in questions within the shoulder category, with 90.9% correct. Bard performed best in the sports category, with 65.4% correct. ChatGPT performed above the published mean of Accreditation Council for Graduate Medical Education orthopedic resident test-takers (66%). There is significant variability in the accuracy of publicly available AI models on the OITE. AI generative language software may play numerous potential roles in the future in orthopedic education, including simulating patient presentations and clinical scenarios, customizing individual learning plans, and driving evidence-based case discussion. Further research and collaboration within the orthopedic community is required to safely adopt these tools and minimize risks associated with their use. [Orthopedics. 2024;47(3):e146-e150.].

Improving the Load Carrying Capacity through Asymmetric Spur Gear using WC-Fe Metal Matrix Composite for Automobile Applications

Gears are the components that have been used for a century to transmit power from one place to another place. Symmetric spur gears are commonly used in the gearbox to transmit power between two parallel shafts. In order to increase the load carrying capacity of the spur gear with reduced noise and vibration, its profile can be modified. This can be achieved by changing the gear tooth design into asymmetric form. Asymmetrically toothed gears are used in power transmission for transmitting the power in one direction. These teeth help to improve the load carrying and power transmitting capacity of the gear. The strength can be further increased by changing the material used in gears. This can be made possible by using Metal Matrix Composite as a gear material. The metal matrix composites have high stiffness and strength to weight ratio compared to the Alloy Steel. The main objective of this project is to increase the load carrying capacity of the spur gear by using WC-Fe metal matrix composite material. The symmetric and asymmetric gear modeling has been done for existing car gear (Maruthi 800) using Ansys parametric design language software. The contact stress, bending stress and von Mises stress of the composite, as well as conventional gear material, is analyzed and the results are compared to find the percentage increase in strength of the gear.

LncRNAs associated with lymph node metastasis in thyroid cancer based on TCGA database

ObjectiveLong non-coding RNA (lncRNA), especially RNA associated with lymph node metastasis, plays an important role in the development of cancer. Identifying metastasis related lncRNAs and exploring their clinical significance can guide the treatment and prognosis of thyroid cancer patients. MethodsRNA expression and clinical data of thyroid cancer was derived from The Cancer Genome Atlas (TCGA) database, while the survival data was obtained from the ULCAN database. R language and SPSS software were used to analyze the correlation between lncRNA and lymph node metastasis of thyroid cancer and the lncRNAs associated with lymph node metastasis were screened. Result10 lncRNAs showed significant differential expression in thyroid cancer with and without lymph node metastasis. Four lncRNAs (LRRC52-AS1, AP002358.1, AC004847.1, and AC254633.1) were overexpressed in metastatic thyroid cancer, while six lncRNAs (SLC26A4-AS1, LINC01886, LINC01789, AF131216.3, AC062015.1, and AL031710.1) were underexpressed. The expression levels of these lncRNAs were associated with the clinical staging of tumors. Cox regression analysis further showed that elevated expression levels of AP002358.1 and LRRC52-AS1 were associated with poor prognosis in patients with thyroid cancer. In addition, analysis of the UALCAN database indicated that these two lncRNAs were significantly overexpressed in thyroid cancer compared to other cancers, and the expression levels of AF131216.3 and AL031710.1 were associated with progression-free survival in thyroid cancer patients. ConclusionThese lncRNAs may play crucial roles in the development and progression of thyroid cancer and could serve as potential markers for predicting tumor metastasis, clinical stage, and patient prognosis.

Developing Multimedia-Call in Writing Using Field Trip Animation Model for the Eight - Graders at SMPIT Al Mumtaz, Indonesia

This research aimed to develop Multimedia Computer Assisted Language Learning (Multimedia CALL) using a field trip animation model (FTA model) into supplementary material for the eighth graders in writing recount text. It was a research and development study. The research subjects were 8th-graders from both homogeneous gender classes of SMPIT Al Mumtaz Pontianak. The research procedure systematically comprised need analysis, needs exploration, the contextual realization of the materials, pedagogical materials development, the physical materials design, and materials evaluation. The needs analysis results revealed that they needed the supplementary writing material, providing integrated reading and listening practices, along with multi facilities so that they were able to compose a topic about a sightseeing trip for 200 words or above. Therefore, the researcher designed four serial and contextual writing learning units, enhanced by the enriched multimedia CALL tools in the material. Besides, the material evaluation found the material was appropriate and practical for the students to write a recount text.Keywords: Development, writing learning material, recount text, field trip animation based model, and Multimedia CALL

Digital Technologies in Language Education: A Comprehensive Review and Analysis

This systematic literature review examines the role and efficacy of digital storytelling (DST), the robot-DST strategy, and the normalization of computer-assisted language learning (CALL) in language education. The review is based on a range of studies published between 2019 and 2023 and follows the PRISMA approach for systematic reviews and meta-analysis. The analysis includes the evaluation of training, validation, and testing stages, with the search employing the keywords "educational technologies" to identify relevant articles. The review's findings highlight the potential of digital storytelling as a multimodal approach to language education. However, the limitations of traditional DST methods are also scrutinized. To address these limitations, the study proposes a robot-based DST approach, robot-DST, to enhance student engagement and promote interaction. The effectiveness of this approach is evaluated through a quasi-experimental study conducted in an English as a Foreign Language (EFL) course, comparing it with the conventional animation-based DST approach. Furthermore, the review explores the normalization of computer-assisted language learning (CALL) and the evolving communicative competencies needed for the digital generation. It also delves into the role of digital technology in reshaping academic journals and emphasizes the importance of integrating digital tools in reading instruction within university curricula. While acknowledging the existing inadequacies in current methodologies, the study serves as an inspiration for future researchers. It provides a solid foundation for developing and implementing innovative solutions in language education. In conclusion, this systematic literature review sheds light on the transformative role of digital technologies in language education. It highlights the potential of digital storytelling, introduces the robot-DST strategy as an alternative approach, and explores the normalization of CALL. The review emphasizes the need for integrating digital tools and fostering evolving communicative competencies to meet the demands of the digital generation. It also underscores the importance of further research and innovation in developing effective solutions for language education.

Effectiveness of AI Integration into Computer-Assisted Language Learning (CALL) on Student Writing Skills Based on Gender

This research has evaluated the efficacy of AI in CALL to improve writing among students by gender. The analysis involved a literature review on how AI and processing have made an impact on writing and it’s utilized to augment writing of the English language learners. It has reviewed an inspection of how educational technology affects men and women disparately. The result proved that integrating AI in technology enhances writing quality of language learners, regardless of their sex. It has exposed the nitty-gritty of gender, technology use and its effectiveness. It stipulates that in the imbuing of CALL on the basis of student demographics, gender-tailored approaches are essential. Moreover, policies and interventions in CALL, need to accommodate gender discrepancies to allow for maximum effectiveness. It is also crucial to delve more deeply into the after-effects of AI infused CALL over time, such as constructing intervention tools attuned with genders. Also, inspecting the fine-tuned effects of integrating AI on student writing, over longer periods would yield insights, into fashioning optimal CALL strategies, suited to learner populations.

FPGAs memory synchronization and performance evaluation using the open computing language framework

&lt;p&gt;One advantage of the open computing language (OpenCL) software framework is its ability to run on different architectures. Field programmable gate arrays (FPGAs) are a high-speed computing architecture used for computation acceleration. This work develops a set of eight benchmarks (memory synchronization functions, explained in this study) using an OpenCL framework to study the effect of memory access time on overall performance when targeting the general FPGA computing platform. The results indicate the best synchronization mechanism to be adopted to synthesize the proposed design on the FPGA computation architecture. The proposed research results also demonstrate the effectiveness of using a task-parallel model approach to avoid using high-cost synchronization mechanisms within proposed designs that are constructed on the general FPGA computation platform.&lt;/p&gt;

The use of information technology for analysis and prediction of climate changes

The article provides a brief overview of the issue of global warming and the factors that influencing climate change. The relevance of the research lies in the need for a comprehensive analysis of climate data and prediction of further trends, both in the short term and the long term, as climate affects evolutionary processes, biosphere balance, the availability of resources essential for the functioning of the technosphere, the amount of primary production produced by producers, all of which collectively ensure the existence of human civilization. Significant fluctuations in the climate, both towards warming and cooling, can disrupt stability and lead to the destruction of the technosphere, economic and social upheavals. The research is based on previous studies conducted using data from 1 100 meteorological stations in Australia, which showed the need to revise the approach to grouping monitoring stations: trends in average temperature changes across the continent, and monitoring stations grouped according to their distance from the coast, showed a general synchronicity of warming and cooling periods, but different dynamic patterns in recent decades. It was decided to study the climate data of one state (Victoria) and compare the results with previous studies. Python programming language packages were used for data processing, analysis, visualization, and forecasting. Data from two monitoring stations in cities located in the south and north of the state were separately analyzed, showing a general trend of slight warming. The trend in temperature changes in the state showed a pattern different from the continental dynamics obtained in previous studies, which confirmed the validity of the chosen approach to studying the climate on the continent. Based on the information obtained, the average temperature was predicted for both the entire state and selected cities.

Adopting Gartner’s hype cycles to investigate the lifespan of computer assisted language learning from EFL learners' perspectives

It is crucial to study how L2 learners use technology when examining the lifespan technology in L2 pedagogy. Therefore, we adopted Gartner’s hype cycles to investigate the lifespan of CALL from the perspectives of EFL learners. To this end, we utilized an explanatory narrative design and gathered and analysed the perspectives of 87 EFL learners regarding the CALL lifespan using autobiographical narratives and semi-structured interviews. The results of the deductive thematic analysis presented motivating and demotivating factors that were asserted to affect EFL learners’ uptake of CALL technologies. Moreover, the findings revealed that EFL learners had fallacies about CALL in the first stages of using technology for L2 learning and tended to reduce those fallacies later on. Therefore, it can be concluded that EFL learners start their use of CALL with some misconceptions stemming from the motivating factors of CALL, continue their use of CALL by facing some demotivating factors originating from fallacies about CALL that they have already committed, and finalise their use of CALL by exploring about CALL features that help them avoid their fallacies. The study has implications to shorten the time of reaching the awareness zone by the L2 learners.

Using model-driven engineering to automate software language translation

The porting or translation of software applications from one programming language to another is a common requirement of organisations that utilise software, and the increasing number and diversity of programming languages makes this capability as relevant today as in previous decades. Several approaches have been used to address this challenge, including machine learning and the manual definition of direct language-to-language translation rules, however the accuracy of these approaches remains unsatisfactory. In this paper we describe a new approach to program translation using model-driven engineering techniques: reverse-engineering source programs into specifications in the UML and OCL formalisms, and then forward-engineering the specifications to the required target language. This approach can provide assurance of semantic preservation, and additionally has the advantage of extracting precise specifications of software from code. We provide an evaluation based on a comprehensive dataset of examples, including industrial cases, and compare our results to those of other approaches and tools. Our specific contributions are: (1) Reverse-engineering source programs to detailed semantic models of software behaviour, to enable semantically-correct translations and reduce re-testing costs; (2) Program abstraction processes defined by precise and explicit rules, which can be edited and configured by users; (3) A set of reusable OCL library components appropriate for representing program semantics, and which can also be used for OCL specification of new applications; (4) A systematic procedure for building program abstractors based on language grammars and semantics.

Can didactic audiovisual translation enhance intercultural learning through CALL? Validity and reliability of a students’ questionnaire

PurposeThis study aims to delve into the interplay between didactic audiovisual translation (DAT) and computer-assisted language learning (CALL), exploring their combined impact on the development of intercultural competence (IC) among learners of English as a foreign language (EFL).Design/methodology/approachUsing a quasi-experimental approach with a quantitative research design, the study analyses the outcomes of a questionnaire answered by 147 students across 15 language centres in Spanish Universities. These participants actively engaged in completing the lesson plans of the Traducción audiovisual como recurso didáctico en el aprendizaje de lenguas extranjeras project, a Spanish-Government funded research initiative aimed at assessing the effects of DAT on language learning.FindingsThe current study confirms the reliability of the instrument developed to measure students’ perceived improvement. Beyond validating the research tool, the findings of the current study confirm the significant improvement in intercultural learning achieved through DAT, effectively enhancing students’ motivation to engage in language learning.Research limitations/implicationsThe current research solely examines students enrolled in higher education language centres. This paper closes with a CALL for additional research, including participants from other educational stages, such as primary or secondary education. In the broader context of CALL research, this study serves as a valuable contribution by exploring the potential of DAT in fostering IC in EFL settings.Originality/valueThis research confirms the potential of DAT and CALL to promote students’ learning process, as the combination of these approaches not only yields linguistic benefits but also intercultural learning.

An FPGA‐based tool for supporting the design, modeling, and evaluation of hybrid object recognition systems on computer engineering courses

AbstractThe field of computer vision is characterized by computationally intensive algorithms and techniques with strict real‐time requirements. Field programmable gate arrays (FPGAs) are based on a concurrent paradigm which allows the design of efficient hardware architectures and has positioned FPGAs as an ideal device for implementing compute‐intensive applications. For this reason, FPGA technology has had a great impact in areas such as computer vision, where one of the main objectives for researchers working in this field is to create efficient automatic object recognition systems. Therefore, the need to provide undergraduates with the necessary skills to design FPGA‐based object recognition systems is evident. With this aim in mind, it is essential that specialization courses related to the design of these systems include the required resources for the student to apply the theoretical knowledge in solving practical problems. In this article, we present a development tool designed to help students, teachers, and researchers during the design‐modeling‐implementation process of object recognition systems based on FPGAs. The proposed tool operates under a modular approach as this facilitates the working on any of the phases of a recognition system and it is considered as a hybrid because the other phases can be developed using a software language. An empirical evaluation involving undergraduates enrolled in a Computer Engineering program was conducted to create a hardware architecture for the DAISY descriptor that uses the homogeneous features of objects immersed in images to produce an efficient representation. By considering similar descriptors such as Scale‐Invariant Feature Transform (SIFT) and Histogram of Oriented Gradients (HOG), DAISY is computed by convolving orientation maps instead of using weighted sums of gradient norms, which offers the same kind of invariance at a lower computational cost for the dense case. The results obtained during such an evaluation indicated that students consider this FPGA‐based tool to be an alternative to receiving practical training on designing systems for solving problems related to the area of object recognition.

Technology-mediated task-based language teaching: a CALL evaluation framework and its pedagogical implications

This paper proposes an updated framework for the evaluation of the computer-assisted language learning (CALL) framework, further developed from Chapelle (2001) and González-Lloret and Ortega (2014). Based on a review of prominent previous CALL evaluation frameworks, an exploration of relevant literature in formal evaluation and my own first-hand practical experience, 1 this paper provides an updated computer-mediated task evaluation framework to aid student language learning. The current paper makes use of a hybrid evaluation framework drawing from Chapelle (2001) and González-Lloret and Ortega (2014), identifying and addressing gaps in their frameworks. The proposed CALL framework is based on nine criteria: primary focus on meaning, goal-orientation, learner autonomy, affective dimension, authenticity, reflective learning, learner fit, positive impact, and practicality. The chosen criteria permit the elaboration of an evaluation framework that takes recent research findings on best practices in the design of CALL tasks into account. This paper provides a detailed explanation of the proposed CALL evaluation framework and pedagogical design, which will allow CALL designers and teachers to assess the design and evaluate the effectiveness of their technology-mediated language tasks.

Implementation of thyroid eye disease registry in Iran: rationale and research protocol.

To describe the implementation of a registry system for patients with thyroid eye disease (TED) in Iran to obtain more information about its nature, prevalence, and annual incidence, as well as extend insight into the etiology, pathogenesis, and eventually make an accurate prognosis of different medical or surgical treatment methods. After receiving approval from the Disease Registry Committee of Iran University of Medical Sciences (IUMS) in 2019 and the Ministry of Health and Medical Education (MOHME) in 2020, the protocol was introduced in three consecutive phases at regional, provincial and national levels. The establishment of a registry committee in Rassoul Akram Hospital, one of the medical centers affiliated to IUMS, was the first step to organizing the registry project's main core. The steering committee included six subgroups of required subject fields. The members are experts in developing a guideline, providing a new dataset, drawing an outline for the next steps, and structuring user-friendly software through several panel discussion meetings. The data is collected from clinical and para-clinical/imaging findings, laboratory evaluations, and their selected treatment strategy, retrospectively and prospectively. The purpose is to broaden our knowledge about the profile of TED; accordingly, data related to patients' demographics, thyroid gland disease (status, duration, treatments, and function tests), general medical and ocular history, along with visual/ocular exams resulting TED status are collected and recorded in a 2- language software. The web-based software system is accessible at https://orc.iums.ac.ir . To maintain data security, prioritized user access was defined for different members. Furthermore, diverse methods, such as employing trained staff and utilizing software validation rules, were implemented to control data quality in every step of data collection, entry, and registration. Medical records of retrospective subjects were also evaluated and entered after accuracy verification. Iran's TED registry provides practitioners with comprehensive data on natural history and phenotype variations in clinical features and outcomes. It facilitates patient recruitment and, consequently, earlier diagnosis on a large scale which helps improve treatment and quality of life for patients.