Natural Language Processing for Medical Texts – A Taxonomy to Inform Integration Decisions into Clinical Practice

2023 | International Conference on Information Systems | Citations: 0

Authors: Braun, Marvin; Kolbe, Lutz; Neumann, Caspar

Abstract: Electronic health records (EHR) have significantly amplified the volume of info ... Expand

Abstract: Electronic health records (EHR) have significantly amplified the volume of information accessible in the healthcare sector. Nevertheless, this information load also translates into elevated workloads for clinicians engaged in extracting and generating patient information. Natural Language Process (NLP) aims to overcome this problem by automatically extracting and structuring relevant information from medical texts. While other methods related to artificial intelligence have been implemented successfully in healthcare (e.g., computer vision in radiology), NLP still lacks commercial success in this domain. The lack of a structured overview of NLP systems is exacerbating the problem, especially with the emergence of new technologies like generative pre-trained transformers. Against this background, this paper presents a taxonomy to inform integration decisions of NLP systems into healthcare IT landscapes. We contribute to a better understanding of how NLP systems can be integrated into daily clinical contexts. In total, we reviewed 29 papers and 36 commercial NLP products. Collapse

Topics: health information system artificial intelligence database system healthcare data information technology infrastructure

Methods: natural language processing computational algorithm information extraction literature sample NLP application

Influence of Twitter on Hydroxychloroquine Medication Prescriptions for COVID-19 Patients

2023 | International Conference on Information Systems | Citations: 0

Authors: Gorthi, Sai Soundarya; Ganju, Kartik; Pinsonneault, Alain

Abstract: Social media is proposed to play a crucial role in healthcare providers' care d ... Expand

Abstract: Social media is proposed to play a crucial role in healthcare providers' care decisions. However, social media information may not always be reliable as false information is prone to virality, and emotional cues may drive information sharing. Hence, in our study, we strive to understand the influence of social media on healthcare providers' care decisions by empirically examining the influence of Twitter discourse regarding Hydroxychloroquine (HCQ) on the actual prescribing rates of the drug in the USA for treating Collapse

Topics: Twitter social media application programming interface Python missing data

Methods: longitudinal research machine learning qualitative coding autocorrelation analysis mixed method

Theories: elaboration likelihood model

Machine Learning based Financial Aid Management Process

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Gottipati, Swapna; Shankararaman, Venky; Rao, Komirisetti Chalapathi; Vetrivillalan, Vennila

Abstract: Advanced programming skills are required for computing courses on merging topic ... Expand

Abstract: Advanced programming skills are required for computing courses on merging topics, and students often struggle to develop these skills to solve complex problems. Faculty tackle this challenge by providing extra lectures, practice sessions, technologies, and education tools. This paper discusses the challenges faced by computer science students in developing advanced programming skills and explores the use of AI chatbots, specifically ChatGPT, as a support tool for learning. We study the engagement and effectiveness of ChatGPT in helping students learn advanced programming skills using two engagement learning frameworks (CIE and MELT) for evaluation. The study involves designing a lab exercise for students to complete using ChatGPT and collecting data through surveys. We present the findings of the study and discuss the limitations of the work. Collapse

Topics: problem solving online learning system artificial intelligence IS effectiveness

Methods: chatGPT survey chatbot sentiment analysis natural language processing

Theories: educational theory learning theory

Improved healthcare disaster decision-making utilizing information extraction from complementary social media data during the COVID-19 pandemic

2023 | Decision Support Systems | Citations: 0

Authors: Kellner, Domenic; Lowin, Maximilian; Hinz, Oliver

Abstract: Managing an extreme event like a healthcare disaster requires accurate informati ... Expand

Abstract: Managing an extreme event like a healthcare disaster requires accurate information about the event's circum­ stances to comprehend the full consequences of acting. However, information quality is rarely optimal since it takes time to determine the information of relevance. The COVID-19 pandemic showed that even official data sources are far from optimal since they suffer from reporting delays that slow decision-making. To support decision-makers with timely information, we utilize data from online social networks to propose an adaptable information extraction solution to create indices helping to forecast COVID-19 case numbers and hospitalization rates. We show that combining heterogeneous data sources like Twitter and Reddit can leverage these sources' inherent complementarity and yield better predictions than those using a single data source alone. We further show that the predictions run ahead of the official COVID-19 incidences by up to 14 days. Additionally, we highlight the importance of model adjustments whenever new information becomes available or the underlying data changes by observing distinct changes in the presence of specific symptoms on Reddit. Collapse

Topics: Twitter Reddit social media pandemic website

Methods: BERT information extraction computational algorithm autoregressive integrated moving average time series analysis

Scalable Sustainability Monitoring of Financial Reports: A Design Science Artifact

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Rath, Oliver; Haase, Frederic; Erlacher, Nina Annika; Schoder, Detlef

Abstract: The United Nations Climate Change (UNCC) report in 2022 warns that the likeliho ... Expand

Abstract: The United Nations Climate Change (UNCC) report in 2022 warns that the likelihood of global warming exceeding 1.5°C by 2026 has surpassed 50%. Climate change is a global problem that requires collective action, and companies have a significant role to play in mitigating climate change. Companies have already started to incorporate climate change risk and liabilities in their annual reports. Monitoring a company's progress in transitioning to sustainability can help stakeholders make informed decisions. However, existing approaches for sustainability monitoring of annual reports are limited in scalability, mainly because of the manual steps involved. Therefore, we designed and evaluated a more scalable artifact using state-of-the-art natural language processing (NLP) techniques to monitor companies' sustainability targets based on their annual reports. This work presents a prototype that improves upon the current state of practice and contributes to the body of knowledge by outlining key design decisions. Collapse

Topics: usability evaluation criteria information portal computer data storage artificial intelligence

Methods: natural language processing computational algorithm question answering design artifact machine learning

Towards a reconceptualization of data in organizations: a literature review

2023 | European Conference On Information Systems | Citations: 0

Authors: Xu, Daisy; Someh, Ida Asadi; Indulska, Marta

Abstract: Information Systems researchers have sought to demonstrate the strategic value ... Expand

Abstract: Information Systems researchers have sought to demonstrate the strategic value of data in organizations through robust evidence. Over time, the ways data benefit organizations have evolved and become more diverse, yet definitions of data and their value propositions have not kept up and remain disconnected. The field still lacks clear understanding of various roles data play in organizations and how to define them. This paper presents a comprehensive review of related literature in the Information Systems and Management fields from the past two decades. We first conduct a systematic literature search and organize them into key research themes by the purpose of data use. We then propose a reconceptualization of data that takes into account their distinct features. Our aim is to provide an explanation for the unique nature of data and the diverse sources of their value in organizations. Collapse

Topics: decision making value creation business process management innovation management organizational context

Methods: literature study design artifact literature sample synthesis theory development

AI for Connectivism Learning - Undergraduate Students’ Experiences of ChatGPT in Advanced Programming Courses

2023 | Americas Conference on Information Systems | Citations: 0

Authors: Gottipati, Swapna; Shim, Kyong Jin; Shankararaman, Venky

Abstract: Advanced programming skills are required for computing courses on merging topic ... Expand

Abstract: Advanced programming skills are required for computing courses on merging topics, and students often struggle to develop these skills to solve complex problems. To address this challenge, faculty members provide additional lectures, practice sessions, and educational technology tools. This paper discusses the challenges faced by computer science students in developing advanced programming skills and explores the use of AI chatbots, specifically ChatGPT, as a support tool for learning. We study the engagement and effectiveness of ChatGPT in helping students learn advanced programming skills using two engagement learning frameworks (CIE and MELT) for evaluation. The study involves designing a computing lab exercise (design and code questions) for students to complete using ChatGPT and collecting data through surveys. The findings provide initial evidence that ChatGPT can be an effective tool for supporting student learning in advanced programming courses. Collapse

Topics: problem solving artificial intelligence online learning system IS effectiveness

Methods: chatGPT survey sentiment analysis chatbot natural language processing

Theories: educational theory learning theory

Just What the Doctor Ordered – Towards Design Principles for NLP-Based Systems in Healthcare

2022 | DESRIST | Citations: 0

Authors: Braun, Marvin; Aslan, Aycan; Ole Diesterhöft, Till; Greve, Maike; Benedikt Brendel, Alfred; Kolbe, Lutz M.

Abstract: Patient data is mainly transmitted in the form of unstructured free texts in med ... Expand

Abstract: Patient data is mainly transmitted in the form of unstructured free texts in medical documentation. Natural language processing (NLP)-based systems can help to structure and extract information from these free texts to support the work of healthcare professionals. However, the healthcare sector must meet certain information quality requirements to comply with regulations and provide optimal patient care. Therefore, we argue that a design guideline is needed to tailor NLP-based systems to the unique requirements of clinical processes and to catalyze the practical application of such systems. In this paper, we report the results of a design science research study, focusing on the requirements of NLP-based systems used by healthcare professionals. In doing so, we shed light on the needs of practitioners when working with sophisticated NLP-based systems that extract and analyze text-based information from medical documentation. By providing evaluated, testable propositions and detailed design principles, we support the practical endeavor of such systems. Collapse

Topics: healthcare data health information system perceived usefulness usability knowledge base

Methods: natural language processing design principle qualitative interview design artifact computational algorithm

MEET YOUR NEW COLLE(AI)GUE – EXPLORING THE IMPACT OF HUMAN-AI INTERACTION DESIGNS ON USER PERFORMANCE

2022 | European Conference On Information Systems | Citations: 0

Authors: Braun, Marvin; Greve, Maike; Riquel, Johannes; Brendel, Alfred Benedikt; Kolbe, Lutz

Abstract: Artificial Intelligence (AI) has an increasing impact on industries, establishi ... Expand

Abstract: Artificial Intelligence (AI) has an increasing impact on industries, establishing a new way of solving tasks and automating work routines. While AI-based systems have become new colleagues for some processes, the tasks of some humans have shifted towards supervising AI. Essentially, humans need to adapt to a new form of interaction with AI-based systems because AI functioning is more similar to cognitive processes of humans than traditional information systems, e.g., in terms of their intransparent decision making. Previous research indicates that AI adds new challenges to human-computer interaction, and new frameworks for human-AI interaction are developed. However, current research lacks empirical research on the design of such interactions. We conducted a 2x2x2 experiment of AIsupported information extraction and measured the ability of participants to validate the extracted information by the AI. Our results indicate that the design of human-AI interaction significantly impacts users' supervising performance.interaction and the current state of research. Second, the SDT is explained and applied to derive hypotheses regarding human-AI interaction. Collapse

Topics: artificial intelligence human AI collaboration decision support system human computer interaction human resource management

Methods: experiment ANOVA parametric test information extraction theoretical contribution

Theories: signal detection theory

LET'S GET PHYSIC(AI)L – TRANSFORMING AI-REQUIREMENTS OF HEALTHCARE INTO DESIGN PRINCIPLES

2022 | European Conference On Information Systems | Citations: 0

Authors: Braun, Marvin; Harnischmacher, Christine; Lechte, Henrik; Riquel, Johannes

Abstract: As healthcare's digitization advances, artificial intelligence (AI) techniques ... Expand

Abstract: As healthcare's digitization advances, artificial intelligence (AI) techniques offer opportunities to improve medical care. In addition to the much-discussed potential in diagnostics, AI-based systems can further support processes in clinics or comparable healthcare facilities, helping to improve medical, organizational, and administrative processes. Nevertheless, apart from single use-cases, AI in healthcare is still not unleashing its full potential. To empower the technology and provide a guideline for developers but also other entities such as medical institutions, we derive and plan to validate design principles guiding the design of AI-based systems specifically operating in clinics and healthcare facilities. In this research in progress study, we conduct the first two phases of the DSR approach by identifying requirements in literature and transforming these into design principles. By doing so, we provide a collection of literature-based design principles that need to be considered when implementing AI-based systems into healthcare contexts. Collapse

Topics: artificial intelligence health information system

Methods: design principle literature study qualitative interview literature sample computational algorithm