Automatic Derivation of a Decision Tree to Represent Guideline-Based Therapeutic Strategies for the Management of Chronic Diseases

2005 ◽  
pp. 131-135 ◽  
Author(s):  
Brigitte Séroussi ◽  
Jacques Bouaud ◽  
Jean-Jacques Vieillot
Keyword(s):  
Decision Tree ◽  
Chronic Diseases ◽  
Therapeutic Strategies

scholarly journals The Ageing Endothelium

2021 ◽  
Author(s):  
Ka Ka Ting ◽  
Paul Coleman ◽  
Yang Zhao ◽  
Mathew A Vadas ◽  
Jennifer R Gamble
Keyword(s):  
Chronic Diseases ◽  
Cellular Senescence ◽  
Vascular Endothelium ◽  
Vascular Diseases ◽  
Therapeutic Strategies ◽  
Metabolic Changes ◽  
Age Related

Cellular senescence is now recognised as one of the hallmarks of ageing. Herein, we examine current findings on senescence of the vascular endothelium and its impacts on age-related vascular diseases. Endothelial senescence can result in systemic metabolic changes, implicating senescence in chronic diseases such as diabetes, obesity and atherosclerosis. Senolytics, drugs that eliminate senescent cells, afford new therapeutic strategies for control of these chronic diseases.

scholarly journals Mining Sequential Risk Patterns for Early Assessment of COPD

2019 ◽  
pp. 496-502
Author(s):  
Saniya PK ◽  
Bineesh V.
Keyword(s):  
Decision Tree ◽  
Chronic Diseases ◽  
Pattern Mining ◽  
Stage Iv ◽  
Severe Illness ◽  
Chronic Obstructive ◽  
Early Assessment ◽  
Obstructive Pulmonary Disease ◽  
Clinical Records ◽  
Risk Pattern

Nowadays, chronic diseases have been among the major concerns in medical fields since they may cause heavy burden on healthcare resources and disturb the quality of life. Chronic Obstructive Pulmonary Disease (COPD) is one kind of popular chronic diseases. COPD takes long period to evolve from mild symptoms (Stage I) to severe illness (Stage IV) and death. Earlier the disease is detected, the better the scope for effective treatment and improved control of symptom development. Therefore, the early of COPD is beneficial for better treatment. The paper examines the novel system for early appraisal on chronic illnesses by mining sequential risk patterns with interim data from diagnostic clinical records utilizing sequential rules mining and classification modelling systems. The system consists of four phases namely data pre-processing, risk pattern mining, classification modelling. SPADE algorithm and CBS algorithm used for risk pattern mining and classification. Decision tree algorithm is compared with the SPADE algorithm, and SPADE showing a better accuracy when comparing with decision tree.

Novel Therapeutic Strategies for the Treatment of Chronic Diseases

2019 ◽  
Vol 26 (16) ◽  
pp. 2788-2790
Author(s):  
Gianluca Testa ◽  
Fabiana Passaro ◽  
Aldo Cinquegrana ◽  
Melania Palma ◽  
Pasquale Abete ◽  
...  
Keyword(s):  
Chronic Diseases ◽  
Therapeutic Strategies ◽  
Novel Therapeutic Strategies ◽  
Novel Therapeutic

scholarly journals Exploring New Kingdoms: The Role of Extracellular Vesicles in Oxi-Inflamm-Aging Related to Cardiorenal Syndrome

Antioxidants ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 78
Author(s):  
Cristina Mas-Bargues ◽  
Matilde Alique ◽  
María Teresa Barrús-Ortiz ◽  
Consuelo Borrás ◽  
Raquel Rodrigues-Díez
Keyword(s):  
Oxidative Stress ◽  
Signaling Pathways ◽  
Chronic Diseases ◽  
Extracellular Vesicles ◽  
Cardiorenal Syndrome ◽  
Therapeutic Strategies ◽  
Abundant Evidence ◽  
Underlying Mechanisms

The incidence of age associated chronic diseases has increased in recent years. Although several diverse causes produce these phenomena, abundant evidence shows that oxidative stress plays a central role. In recent years, numerous studies have focused on elucidating the role of oxidative stress in the development and progression of both aging and chronic diseases, opening the door to the discovery of new underlying mechanisms and signaling pathways. Among them, senolytics and senomorphics, and extracellular vesicles offer new therapeutic strategies to slow the development of aging and its associated chronic diseases by decreasing oxidative stress. In this review, we aim to discuss the role of extracellular vesicles in human cardiorenal syndrome development and their possible role as biomarkers, targets, or vehicles of drugs to treat this syndrome.

scholarly journals Multifactorial Basis and Therapeutic Strategies in Metabolism-Related Diseases

Nutrients ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 2830
Author(s):  
João V. S. Guerra ◽  
Marieli M. G. Dias ◽  
Anna J. V. C. Brilhante ◽  
Maiara F. Terra ◽  
Marta García-Arévalo ◽  
...  
Keyword(s):  
Chronic Diseases ◽  
Molecular Mechanisms ◽  
Activity Patterns ◽  
Therapeutic Strategies ◽  
Research Progress ◽  
Pharmacological Interventions ◽  
Ongoing Research ◽  
Related Risk ◽  
Main Factors ◽  
The Relationship

Throughout the 20th and 21st centuries, the incidence of non-communicable diseases (NCDs), also known as chronic diseases, has been increasing worldwide. Changes in dietary and physical activity patterns, along with genetic conditions, are the main factors that modulate the metabolism of individuals, leading to the development of NCDs. Obesity, diabetes, metabolic associated fatty liver disease (MAFLD), and cardiovascular diseases (CVDs) are classified in this group of chronic diseases. Therefore, understanding the underlying molecular mechanisms of these diseases leads us to develop more accurate and effective treatments to reduce or mitigate their prevalence in the population. Given the global relevance of NCDs and ongoing research progress, this article reviews the current understanding about NCDs and their related risk factors, with a focus on obesity, diabetes, MAFLD, and CVDs, summarizing the knowledge about their pathophysiology and highlighting the currently available and emerging therapeutic strategies, especially pharmacological interventions. All of these diseases play an important role in the contamination by the SARS-CoV-2 virus, as well as in the progression and severity of the symptoms of the coronavirus disease 2019 (COVID-19). Therefore, we briefly explore the relationship between NCDs and COVID-19.

scholarly journals Machine Learning Implementation of a Diabetic Patient Monitoring System Using Interactive E-App

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Malik Bader Alazzam ◽  
Hoda Mansour ◽  
Fawaz Alassery ◽  
Ahmed Almulihi
Keyword(s):  
Physical Activity ◽  
Machine Learning ◽  
Type 2 Diabetes ◽  
Decision Tree ◽  
Chronic Diseases ◽  
Lifestyle Changes ◽  
Self Management ◽  
Healthy Weight ◽  
Time Activity

Lifestyle influences morbidity and mortality rates in the world. Physical activity, a healthy weight, and a healthy diet are key preventative health behaviours that help reduce the risk of developing type 2 diabetes and its complications, such as cardiovascular disease. A healthy lifestyle has been shown to prevent or delay chronic diseases and their complications, but few people follow all recommended self-management behaviours. This work seeks to improve knowledge of factors affecting type 2 diabetes self-management and prevention through lifestyle changes. This paper describes the design, development, and testing of a diabetes self-management mobile app. The app tracked dietary consumption and health data. Bluetooth movement data from a pair of wearable insole devices are used to track carbohydrate intake, blood glucose, medication adherence, and physical activity. Two machine learning models were constructed to recognise sitting and standing. The SVM and decision tree models were 86% accurate for these tasks. The decision tree model is used in a real-time activity classification app. It is exciting to see more and more mobile health self-management apps being used to treat chronic diseases.

Patterns and Related Influencing Factors of Multiple Chronic Diseases Among the Elderly Based on Data Mining in Shanxi, China

2020 ◽  
Author(s):  
Chichen Zhang ◽  
Shujuan Xiao ◽  
Lei Shi ◽  
Xiao Zheng ◽  
Fang Dong ◽  
...  
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Chronic Diseases ◽  
Influencing Factors ◽  
The Elderly ◽  
Education Level ◽  
Public Health Issue ◽  
Tree Model ◽  
Genetic History ◽  
Multiple Chronic Diseases

Abstract Background: The presence of multiple chronic diseases has become a public health issue worldwide. The study aimed to explore the patterns and related influencing factors of multiple chronic diseases among the elderly so as to provide a scientific reference for the health management strategy, which is dedicated to the prevention and intervention for multiple chronic diseases. Methods: A cross-sectional study, which used a multi-stage random sampling way, was conducted among 3266 elderly aged 60 years and above in Shanxi. A chi square test was used to compare the sociodemographic factors. The data mining methods, including association rule and decision tree, were performed to explore the patterns and related influencing factors of multiple chronic diseases in the elderly.Results: The prevalence of multiple chronic diseases was 30.31%. According to the results of the association rules, there were 10 association patterns screened out. The first five multiple chronic disease patterns were atherosclerosis and hypertension, coronary heart disease and hypertension, diabetes and hypertension, stroke and hypertension, eye disease and hypertension. The decision tree model selected 5 related influencing factors of multiple chronic diseases, including age, smoking, family genetic history, fresh fruit intake frequency and education level, simultaneously generating 9 influence rules.Conclusions: Multiple chronic diseases were prevalent among the elderly, which patterns mainly consisted of two or three chronic diseases. Regarding the unmodifiable related influencing factors, including an older age, a family genetic history, and low education level, relevant departments should help the elderly to establish prevention knowledge and raise awareness of strongly related chronic diseases, so as to reduce the incidence and adverse consequences.

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