Cardiometabolic risk prediction algorithms for young people with psychosis: a systematic review and exploratory analysis

BI Perry, R Upthegrove, O Crawford… - Acta Psychiatrica …, 2020‏ - Wiley Online Library
Objective Cardiometabolic risk prediction algorithms are common in clinical practice. Young
people with psychosis are at high risk for develo** cardiometabolic disorders. We aimed …

Machine learning based unified framework for diabetes prediction

SMH Mahmud, MA Hossin, MR Ahmed… - Proceedings of the …, 2018‏ - dl.acm.org
Machine learning gained a significant position in healthcare services (HCS) due to its ability
to improve the disease prediction in HCS. Machine learning techniques and artificial …

A survey on data mining techniques used in medicine

SM Birjandi, SH Khasteh - Journal of diabetes & metabolic disorders, 2021‏ - Springer
Data mining is the process of analyzing a massive amount of data to identify meaningful
patterns and detect relations, which can lead to future trend prediction and appropriate …

[HTML][HTML] Patient-generated data analytics of health behaviors of people living with type 2 diabetes: sco** review

MS Nagpal, A Barbaric, D Sherifali, PP Morita… - JMIR …, 2021‏ - diabetes.jmir.org
Background Complications due to type 2 diabetes (T2D) can be mitigated through proper
self-management that can positively change health behaviors. Technological tools are …

A proposed model for lifestyle disease prediction using support vector machine

M Patil, VB Lobo, P Puranik, A Pawaskar… - 2018 9th …, 2018‏ - ieeexplore.ieee.org
Diseases that are associated with the way a person or group of people live are known as
lifestyle diseases. Healthcare industry collects enormous disease-related data that is …

[HTML][HTML] Cocreation of massive open online courses to improve digital health literacy in diabetes: pilot mixed methods study

Y Alvarez-Perez, L Perestelo-Perez… - JMIR …, 2021‏ - diabetes.jmir.org
Background: Self-management education is a fundamental aspect in the health care of
people with diabetes to develop the necessary skills for the improvement of health …

Obesity level prediction based on data mining techniques

A Alqahtani, F Albuainin, R Alrayes… - … Journal of Computer …, 2021‏ - koreascience.kr
Obesity affects individuals of all gender and ages worldwide; consequently, several studies
have performed great works to define factors causing it. This study develops an effective …

Obesity related disease prediction from healthcare communities using machine learning

NC Pereira, J D'souza, P Rana… - 2019 10th International …, 2019‏ - ieeexplore.ieee.org
In addition to the rapid growth of Machine Learning in biomedical and healthcare
communities, the accurate analysis of medical data benefits early disease detection, patient …

[PDF][PDF] Analyzing student's learning interests in the implementation of blended learning using data mining

Y Ariyanto, B Harijanto, A Asri - 2020‏ - learntechlib.org
Blended Learning combines teaching and learning activities in the classroom and online
teaching. In its implementation, this learning method requires a lot of data. One of them is the …

Classification and features selection method for obesity level prediction

D Molina Estren, AK De la Hoz Manotas… - 2021‏ - repositorio.cuc.edu.co
Resumen en español Obesity has become one of the world's largest health issues, rich and
poor countries, without exception, have each year larger populations with this condition …