Special Issue “Machine Learning Methods for Biomedical Data Analysis”
1. Introduction
2. Biomedical Diagnosis
3. Biomedical Assistance Tools
4. Health Monitoring
5. Industrial Applications
6. Other Applications
7. Conclusions
Funding
Acknowledgments
Conflicts of Interest
References
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No. of Contribution | Title | Focus | Type of Organization | Country |
---|---|---|---|---|
1 | Prediction of Diabetes Mellitus Progression Using Supervised Machine Learning | Biomedical diagnostics | University | USA |
2 | Prediction of Preterm Labor from the Electrohysterogram Signals Based on Different Gestational Weeks | Biomedical diagnostics | University | Poland, Finlan, Lithuania |
3 | Spatiotemporal eye-tracking feature set for improved recognition of dyslexic reading patterns in children. | Biomedical diagnostics | University | Serbia |
4 | A machine learning approach for predicting non-suicidal self-injury in young adults | Biomedical diagnostics | University, Industry | Spain |
5 | Treatment Outcome Prediction Using Multi-Task Learning: Application to Botulinum Toxin in Gait Rehabilitation | Biomedical care tools | University, Laboratory | France, Pakistan |
6 | Enabling timely medical intervention by exploring health-related multivariate time series with a hybrid attentive model | Biomedical care tools | University, | China |
7 | Estimation of Respiratory Rate during Biking with a Single Sensor Functional Near-Infrared Spectroscopy (fNIRS) System | Health monitoring | University, Industry | Netherlands, Lithuania |
8 | HUMANISE: human-inspired smart management, towards a healthy and safe industrial collaborative robotics | Industrial applications | University, Laboratory | UK, Spain |
9 | Data Fusion-Based Musculoskeletal Synergies in the Grasping Hand | Others | University | USA |
10 | An Interpretable Two-Phase Modeling Approach for Lung Cancer Survivability Prediction | Others | University | USA |
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Caiafa, C.F.; Sun, Z.; Tanaka, T.; Marti-Puig, P.; Solé-Casals, J. Special Issue “Machine Learning Methods for Biomedical Data Analysis”. Sensors 2023, 23, 9377. https://doi.org/10.3390/s23239377
Caiafa CF, Sun Z, Tanaka T, Marti-Puig P, Solé-Casals J. Special Issue “Machine Learning Methods for Biomedical Data Analysis”. Sensors. 2023; 23(23):9377. https://doi.org/10.3390/s23239377
Chicago/Turabian StyleCaiafa, Cesar F., Zhe Sun, Toshihisa Tanaka, Pere Marti-Puig, and Jordi Solé-Casals. 2023. "Special Issue “Machine Learning Methods for Biomedical Data Analysis”" Sensors 23, no. 23: 9377. https://doi.org/10.3390/s23239377
APA StyleCaiafa, C. F., Sun, Z., Tanaka, T., Marti-Puig, P., & Solé-Casals, J. (2023). Special Issue “Machine Learning Methods for Biomedical Data Analysis”. Sensors, 23(23), 9377. https://doi.org/10.3390/s23239377