A Combined-Predictor Approach to Glycaemia Prediction for Type 1 Diabetes

Saiti, Kyriaki; Macaš, Martin; Stechova, Katerina; Piťhová, Pavlína; Lhotská, Lenka

doi:10.1007/978-981-10-9023-3_136

Cited by 2 publications

(1 citation statement)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The aim of the project was interdisciplinary research focused on decision support in diabetic patient treatment. The core is the design of a software prototype (SW)-an application for cell phones-that offers to a diabetic patient treated by an insulin pump an advanced advice on insulin dose based on previous individual experience (self-learning algorithm) [57][58][59]. Inputs for the SW are (1) complex information on food content (including glycaemia index and reflecting the previous patient's glycaemia reaction to the similar type of food); (2) the amount of active insulin (information available from the insulin pump); and (3) additional information on physical activity and stress (psychic, illness, etc.).…”

Section: Intelligent Methods For Evaluation Of Long-term Eeg Recordin...mentioning

confidence: 99%

Artificial Intelligence and Women Researchers in the Czech Republic

Lhotská

Štěpánková

2022

Applied Sciences

View full text Add to dashboard Cite

Artificial intelligence as a research area has been continuously growing for several decades. Many applications were developed in various domains. Medicine and health care have attracted more intensive attention thanks to rapid technological development that has accelerated generation of large volumes of data requiring intelligent analysis and evaluation. This article illustrates, through examples of women researchers and selected AI projects in medicine, the wide spectrum of applications developed during the last fifteen years in the Czech Republic, and in particular at the Czech Technical University in Prague. Women researchers played an important and irreplaceable role since the advent of AI research in the Czech Republic. By their example, they motivated many young female students to join the community and start their research career in the AI area. They frequently participated in research projects led by the senior women researchers. The presented overview of projects illustrates the diversity of the medical area and the potential of AI methods that can be used for solving data- and knowledge-intensive problems. We briefly touch on the AI study programs. In conclusion, we point out the future challenges in AI and its applications in medicine and health care.

show abstract

Section: Intelligent Methods For Evaluation Of Long-term Eeg Recordin...mentioning

confidence: 99%