Results 21 to 30 of about 547,727 (260)

Predicting Ecological Momentary Assessments in an App for Tinnitus by Learning From Each User's Stream With a Contextual Multi-Armed Bandit

Frontiers in Neuroscience, 2022
Ecological Momentary Assessments (EMA) deliver insights on how patients perceive tinnitus at different times and how they are affected by it. Moving to the next level, an mHealth app can support users more directly by predicting a user's next EMA and ...
Saijal Shahania, Vishnu Unnikrishnan, Rüdiger Pryss, Robin Kraft, Johannes Schobel, Ronny Hannemann, Winny Schlee, Myra Spiliopoulou   +7 more
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Bisociative Knowledge Discovery [PDF]

, 2011
Data analysis generally focusses on finding patterns within a reasonably well connected domain of interest. In this article we focus on the discovery of new connections between domains (so called bisociations), supporting the creative discovery process in a novel way.
openaire   +2 more sources

Interactive System for Similarity-Based Inspection and Assessment of the Well-Being of mHealth Users

Entropy, 2021
Recent digitization technologies empower mHealth users to conveniently record their Ecological Momentary Assessments (EMA) through web applications, smartphones, and wearable devices.
Subash Prakash, Vishnu Unnikrishnan, Rüdiger Pryss, Robin Kraft, Johannes Schobel, Ronny Hannemann, Berthold Langguth, Winfried Schlee, Myra Spiliopoulou   +8 more
doaj   +1 more source

Symptom diaries as a digital tool to detect SARS-CoV-2 infections and differentiate between prevalent variants

Frontiers in Public Health, 2022
The COVID-19 pandemic and the high numbers of infected individuals pose major challenges for public health departments. To overcome these challenges, the health department in Cologne has developed a software called DiKoMa.
Barbara Grüne, Sabine Kugler, Sebastian Ginzel, Anna Wolff, Michael Buess, Annelene Kossow, Annelene Kossow, Annika Küfer-Weiß, Stefan Rüping, Florian Neuhann, Florian Neuhann   +10 more
doaj   +1 more source

MatCoupLy: Learning coupled matrix factorizations with Python

SoftwareX, 2023
Coupled matrix factorization (CMF) models jointly decompose a collection of matrices with one shared mode. For interpretable decompositions, constraints are often needed, and variations of constrained CMF models have been used in various fields ...
Marie Roald
doaj   +1 more source

Knowledge Management Challenges in Knowledge Discovery Systems [PDF]

16th International Workshop on Database and Expert Systems Applications (DEXA'05), 2006
Current knowledge discovery systems are armed with many data mining techniques that can be potentially applied to a new problem. However, a system faces a challenge of selecting the most appropriate technique(s) for a problem at hand, since in the real domain area it is infeasible to perform a comparison of all applicable techniques.
Pechenizkiy, M., Tsymbal, A., Puuronen, S.   +2 more
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Sublemma-Based Neural Machine Translation

Complexity, 2021
Powerful deep learning approach frees us from feature engineering in many artificial intelligence tasks. The approach is able to extract efficient representations from the input data, if the data are large enough. Unfortunately, it is not always possible
Thien Nguyen, Huu Nguyen, Phuoc Tran
doaj   +1 more source

Prognostic Prediction through Biclustering-Based Classification of Clinical Gene Expression Time Series

Journal of Integrative Bioinformatics, 2011
The constant drive towards a more personalized medicine led to an increasing interest in temporal gene expression analyzes. It is now broadly accepted that considering a temporal perspective represents a great advantage to better understand disease ...
Carreiro André V., Anunciação Orlando, Carriço João A., Madeira Sara C.   +3 more
doaj   +1 more source

FusionSense: Emotion Classification Using Feature Fusion of Multimodal Data and Deep Learning in a Brain-Inspired Spiking Neural Network

Sensors, 2020
Using multimodal signals to solve the problem of emotion recognition is one of the emerging trends in affective computing. Several studies have utilized state of the art deep learning methods and combined physiological signals, such as the ...
Clarence Tan, Gerardo Ceballos, Nikola Kasabov, Narayan Puthanmadam Subramaniyam   +3 more
doaj   +1 more source

Applications of Artificial Intelligence in the IoT

Applied Sciences
Internet of Things (IoT) systems face various challenges in real-world applications, including operational, performance and security issues [...]
Ahmad Akbari Azirani, Bijan Raahemi
doaj   +1 more source