The use of data in modern healthcare systems are increasing rapidly with the advancement of state-of-the-art information technology. Research in healthcare systems data has received a great deal of attention in recent years from the research community to improve health outcome. Development and deployment of novel and existing data mining and machine learning techniques can have huge benefits for the healthcare systems including early detection, monitoring, prevention, prediction, diagnosis, treatment, and administration of diseases of patients. Data mining and machine learning techniques play an important role in the development of various data-driven technologies for healthcare systems to help healthcare professionals take data-driven decisions to improve health outcome.
The main goal of this research topic is to explore novel and existing data-driven techniques in healthcare relevant for development of innovative data-driven health technology (i.e., to be used for intelligent monitoring and decision support systems, predictive models for prevention, early detection, diagnosis, treatment and prognosis, digital health systems offering novel personalized data collection, treatment plans and interventions). Papers within this research topic should focus on challenges, limitations, opportunities, and potential impact for future healthcare systems from practical, experimental or theoretical perspectives. Papers should emphasize how the stakeholders (i.e., patients and their relatives, healthcare professionals, hospital administrators, etc.) benefit from the proposed technological advances.
We invite researchers and practitioners to submit their latest high-quality work on data-driven health technology including (but not limited to) the following topics:
? AI and machine learning in healthcare
? Transparency, trustworthiness and explainability
? Digital health transformation
? Security and privacy in digital health
? Classification of healthcare data
? Clustering of healthcare data
? Text mining related to healthcare data
? Big data analytics in health
? Regression for prediction in healthcare data
? Prediction using healthcare data
? Analysis of hospital acquired complications
? Social network concepts in healthcare systems
? Impact of technology in healthcare systems
? IoT in healthcare systems
? Wrangling, exploration and cleaning of healthcare data.
? Evaluation and assessment of technology
? Pattern analysis using healthcare data
The use of data in modern healthcare systems are increasing rapidly with the advancement of state-of-the-art information technology. Research in healthcare systems data has received a great deal of attention in recent years from the research community to improve health outcome. Development and deployment of novel and existing data mining and machine learning techniques can have huge benefits for the healthcare systems including early detection, monitoring, prevention, prediction, diagnosis, treatment, and administration of diseases of patients. Data mining and machine learning techniques play an important role in the development of various data-driven technologies for healthcare systems to help healthcare professionals take data-driven decisions to improve health outcome.
The main goal of this research topic is to explore novel and existing data-driven techniques in healthcare relevant for development of innovative data-driven health technology (i.e., to be used for intelligent monitoring and decision support systems, predictive models for prevention, early detection, diagnosis, treatment and prognosis, digital health systems offering novel personalized data collection, treatment plans and interventions). Papers within this research topic should focus on challenges, limitations, opportunities, and potential impact for future healthcare systems from practical, experimental or theoretical perspectives. Papers should emphasize how the stakeholders (i.e., patients and their relatives, healthcare professionals, hospital administrators, etc.) benefit from the proposed technological advances.
We invite researchers and practitioners to submit their latest high-quality work on data-driven health technology including (but not limited to) the following topics:
? AI and machine learning in healthcare
? Transparency, trustworthiness and explainability
? Digital health transformation
? Security and privacy in digital health
? Classification of healthcare data
? Clustering of healthcare data
? Text mining related to healthcare data
? Big data analytics in health
? Regression for prediction in healthcare data
? Prediction using healthcare data
? Analysis of hospital acquired complications
? Social network concepts in healthcare systems
? Impact of technology in healthcare systems
? IoT in healthcare systems
? Wrangling, exploration and cleaning of healthcare data.
? Evaluation and assessment of technology
? Pattern analysis using healthcare data
