A5087320115- Big Data and Business Intelligence
- Artificial Intelligence in Healthcare
- Artificial Intelligence in Healthcare and Education
- Healthcare Systems and Public Health
- Digital Transformation in Industry
- Impact of AI and Big Data on Business and Society
- Ethics and Social Impacts of AI
- Information Systems Theories and Implementation
- Explainable Artificial Intelligence (XAI)
- Scientific Computing and Data Management
- Neural Networks and Applications
- COVID-19 diagnosis using AI
Technical University of Darmstadt
2021
Software (Germany)
2021
Background Recently, machine learning (ML) has been transforming our daily lives by enabling intelligent voice assistants, personalized support for purchase decisions, and efficient credit card fraud detection. In addition to its everyday applications, ML holds the potential improve medicine as well, especially with regard diagnostics in clinics. a world characterized population growth, demographic change, global COVID-19 pandemic, systems offer opportunity make more effective efficient,...
A high-velocity paradigm shift towards Explainable Artificial Intelligence (XAI) has emerged in recent years. Highly complex Machine Learning (ML) models have flourished many tasks of intelligence, and the questions started to away from traditional metrics validity something deeper: What is this model telling me about my data, how it arriving at these conclusions? Previous work uncovered predictive generating explanations contrasting domain experts, or excessively exploiting bias data that...
The recent advent of artificial intelligence (AI) solutions that surpass humans' problem-solving capabilities has uncovered AIs' great potential to act as new type problem solvers. Despite decades analysis, research on organizational solving commonly assumed the solver is essentially human. Yet, it remains unclear how existing knowledge human translates a context with machines. To take first step better understand this novel context, we conducted qualitative study 24 experts explore process...
In a world with constantly growing and aging population, health is precious asset. Presently, machine learning (ML), technological change taking place that could provide high quality healthcare especially, improve efficiency of medical diagnostics in clinics. However, ML needs to be deeply integrated clinical routines which highly differs from the integration previous IT given specific characteristics ML. Since existing literature on adoption scarce, we set up an explorative qualitative...
<sec> <title>BACKGROUND</title> Recently, machine learning (ML) has been transforming our daily lives by enabling intelligent voice assistants, personalized support for purchase decisions, and efficient credit card fraud detection. In addition to its everyday applications, ML holds the potential improve medicine as well, especially with regard diagnostics in clinics. a world characterized population growth, demographic change, global COVID-19 pandemic, systems offer opportunity make more...