Predictive Algorithms for Health

The work carried out in this WP targets the research and development of algorithms and applications for the implementation of a framework to identify, predict, monitor and warn on cardiology, Neurodegenerative diseases and comportamental originated diseases.

Team & Collaborators

• Miguel Castelo Branco | WP leader
• Nuno Garcia
• Nuno Pombo
• Sandeep Pirbhulal | Research fellow, UBI (05/2019-04/2020)
• Henriques Zacarias | PhD Student, UBI
• Virginie Felizardo | PhD Student, UBI
• Igor Matias | MSc Student, UBI
• Mehran Pourvahab | PostDoc

Publications

Journal articles

• Felizardo V., Garcia N., Pombo N., Megdiche I.. Data-based algorithms and models using diabetics real-data for hypoglycaemia prediction – a systematic review. Journal of Biomedical Informatics. (submitted for publication)
• Denysyuk H., Amado J., Gonçalves N., Zdravevski E., Garcia N., Pires I.. (2022). Monitoring of Cardiovascular Diseases: An Analysis of the Mobile Applications Available in the Google Play Store. Electronics 11 (12), 1881.
• Pires I., Denysyuk H., Villasana M., Sá J., Lameski P., Chorbev I., Zdravevski E., Trajkovik V., Morgado J., Garcia N.. (2021). Mobile 5P-medicine approach for cardiovascular patients. Sensors 21 (21), 6986.
• Felizardo V., Machado D., Garcia N., Pombo N., Brandão P.. (2021). Hypoglycaemia Prediction Models With Auto Explanation. IEEE Access 10, 57930-57941.
• Felizardo V., Garcia N., Pombo N., Megdiche I.. (2021). Data-based algorithms and models using diabetics real data for blood glucose and hypoglycaemia prediction–a systematic literature review. Artificial Intelligence in Medicine 118, 102120.
• Yanez C.. (2021). Stepping into the Era of Personal Big Data: a Roadmap to the Design of a Personal Digital Life Coach. OSF Preprints.
• Matias I., Garcia N., Pirbhulal S., Felizardo V., Pombo N., Zacarias H., Sousa M., Zdravevski E.. (2020). Prediction of Atrial Fibrillation using artificial intelligence on Electrocardiograms: A systematic review. Computer Science Review 39, 100334.
• Marques G., Pires I., Garcia N.. (2020). Diabetes Disease through Machine Learning: A comparative study. 4th International Conference on Computer Science and Artificial Intelligence.
• Marques H., Carvalho H., Morgado J., Garcia N., Pires I., Zdravevski E.. (2020). Control and Prevention of Personal Stress. IEEE International Conference on Big Data (Big Data), 3783-3785.
• Popovski G., Ponciano V., Marques G., Pires I., Zdravevski E., Garcia N.. (2020). Personal Digital Life Coach for Physical Therapy. IEEE International Conference on Big Data (Big Data), 3797-3802.
• Tonkovic P., Kalajdziski S., Zdravevski E., Lameski P., Corizzo R., Pires I., Garcia N., Loncar-Turukalo T., Trajkovik V.. (2020). Literature on applied machine learning in metagenomic classification: a scoping review. Biology 9 (12), 453.
• Pires I., Garcia N., Zdravevski E., Lameski P.. (2020). Activities of daily living with motion: A dataset with accelerometer, magnetometer and gyroscope data from mobile devices. Data in brief 33, 106628.
• Pombo N., Silva B., Pinho A., Garcia N.. (2020). Classifier precision analysis for sleep apnea detection using ECG signals. IEEE Access 8, 200477-200485.
• Husic J., Melero F., Barakovic S., Lameski P., Zdravevski E., Maresova P., Krejcar O., Chorbev I., Garcia N., Trajkovik V.. (2020). Aging at work: A review of recent trends and future directions. International journal of environmental research and public health 17 (20), 7659.
• Souza-Pereira L., Pombo N., Ouhbi S., Felizardo V., Garcia N.. (2020). Clinical decision support systems for chronic diseases: A systematic literature review. Computer Methods and Programs in Biomedicine 195, 105565.
• Ponciano V., Pires I., Ribeiro F., Garcia N., Villasana M., Zdravevski E., Lameski P.. (2020). Machine learning techniques with ECG and EEG data: an exploratory study. Computers 9 (3), 55.
• Pires I., Marques G., Garcia N., Flórez-Revuelta F., Ponciano V., Oniani S.. (2020). A research on the classification and applicability of the mobile health applications. Journal of personalized medicine 10 (1), 11.
• Pires I., Marques G., Garcia N., Ponciano V.. (2020). Machine learning for the evaluation of the presence of heart disease. Procedia Computer Science 177, 432-437.
• Pires I., Marques G., Garcia N., Zdravevski E.. (2020). Identification of Activities of Daily Living through Artificial Intelligence: an accelerometry-based approach. Procedia Computer Science 175, 308-314.
• Ponciano V., Pires I., Ribeiro F., Villasana M., Garcia N., Leithardt V.. (2020). Detection of diseases based on Electrocardiography and Electroencephalography signals embedded in different devices: An exploratory study. Brazilian Journal of Development 6 (5).
• Pereira G., Pires I., Marques G., Garcia N., Zdravevski E., Lameski P., Flórez-Revuelta F., Spinsante S.. (2020). Mobile Applications Dedicated for Cardiac Patients: Research of Available Resources. Internet of Things and Big Data Applications, 107-119.
• Pirbhulal S., Pombo N., Felizardo V., Garcia N., Sodhro A., Mukhopadhyay S.. (2019). Towards Machine Learning Enabled Security Framework for IoT-based Healthcare. IEEE International Conference on Sensing Technology, pp. 1-6, IEEE.

PhD thesis

• Henriques Zacarias, PhD student in Biomedicine, UBI. Thesis title, A novel automatic predictive system for Atrial Fibrillation detection in Electrocardiograms. Co-advised by Dr. João Alexandre Lobo Marques (University of São José, Macao) and Dr. Victor Hugo Albuquerque (University of Fortaleza, Brazil). Expected conclusion in June 2023.
• Virginie Felizardo, PhD student in Computer Science and Engineering, UBI. Thesis title, Context-aware algorithms for Diabetes or Prediabetes prediction and diagnosis support in Ambient Assisted Living. Co-adivsed by Dr. Imen Megdiche (Université Paul Sabatier, Toulouse, France). Expected defence in December 2022.

MSc thesis

• Igor Matias, MSc student in Computer Science and Engineering, UBI. Dissertation title, ECG based Prediction Model for Cardiac-Related Diseases using Machine Learning Techniques. Co-supervised by Prof. Miguel Castelo Branco (UBI) and Prof. Eftim Zdravevski (Faculty of Computer Science and Engineering, University Ss. Cyril and Methodius, Skopje, Macedonia). June 2020.

Related activities

• Prontus, project proposal in preparation, with PEGASI, Lda..
• Sandeep Pirbhulal, Analysis of ECG based Random Binary Sequence Generation for Medical Applications, C4 – RINNOVAR – Research and INNOVation seminAR. November 2019. Covilhã, Portugal.

Last Update | Feb 11, 2023 (10:17 PM)