Health Care Data Mining and Analytics

The utilisation of extensive and varied health data is becoming increasingly prevalent in the delivery of enhanced patient care. Concurrently, they present a significant opportunity for the effective distribution of limited healthcare resources. This section presents our most recent research on the numerous applications of health data collection and analysis.

Key Takeaways

The volume of research into innovative applications of artificial intelligence and machine learning (ML) has been increasing at a steady rate over the last few years, indicating the growing potential of the use and application of ML-related software/algorithms in medical care and research (an increase in clinical studies in the field of machine learning).
Risk prediction models can direct preventive measures towards individuals with elevated hospital risk profiles and reduce avoidable admissions. However, they require diverse data sets (Big Data Analytics to reduce preventable hospitalisations).
An increasing number of companies are employing social media platforms such as Twitter for the purpose of engaging in dialogic corporate social responsibility (CSR) communication. This approach allows them to identify the needs of their stakeholders and to foster positive word-of-mouth. In this context, the role of the chief executive officer (CEO) is of particular significance, as they are able to leverage their networks to facilitate interaction and enhance loyalty among customers, communities, and employees. (Corporate Social Responsibility on Twitter)

Ongoing projects

Research hotspots and trends in social media mining and big data

The objective of the study is to identify emerging trends and pertinent subject areas within the domains of social media mining and big data. The objective is to examine the impact of these technologies on health economics and management. Through the use of bibliometric analyses and data mining techniques, we examine academic publications, social media, and big data sources to identify patterns and research priorities. Our objective is to gain insight into the evolving landscape of health-related big data and its impact on political decisions and strategies in health management.

Successfully completed projects

The Application of Social Media Mining in the Context of Pharmaceutical Innovation

The objective of the study was to identify patient needs through social media mining, which is the automated, often AI-supported analysis of social media data.

Article: Social Media Mining of Long-COVID Self-Medication Reported by Reddit Users: Feasibility Study to Support Drug Repurposing
Jonathan Koß, Sabine Bohnet-Joschko, JMIR Formative Research, 2022
This article is available here.

Artificial Intelligence in Healthcare

The objective of the study was to gain insight into the research and development pipeline for algorithmic health innovations.

Article: Rise of Clinical Studies in the Field of Machine Learning: A Review of Data Registered in ClinicalTrials.gov
Claus Zippel, Sabine Bohnet-Joschko, International Journal of Environmental Research and Public Health, 2021
This article is available here.

Magazine Article: KI-basierte Gesundheitsinnovationen auf dem Vormarsch
Sabine Bohnet-Joschko, Claus Zippel, 2021
This article is available here.