scholarly journals Research on Key Technologies of Personalized Intervention for Chronic Diseases Based on Case-Based Reasoning

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Lin Zhang ◽  
Ping Qi
Keyword(s):  
Chronic Disease ◽  
Chronic Diseases ◽  
Case Based Reasoning ◽  
Chronic Patients ◽  
Number Of Patients ◽  
Key Technologies ◽  
The Times ◽  
Case Organization ◽  
Personalized Intervention ◽  
Case Based

In recent years, with the acceleration of industrialization, urbanization, and aging process, the number of patients with chronic diseases in the world is increasing year by year. In China, the number of chronic diseases has increased tenfold in 10 years. The percentage of the disease burden in the whole society accounts for 79.4%. Chronic diseases have become the top killer for Chinese people’s health. However, for chronic diseases, prevention is more important than treatment. It is the best way to keep healthy. Therefore, health intervention is the key to prevent chronic diseases. Especially now, with the spread of COVID-19 pandemic, reducing the times of hospital check-ups and treatments for chronic patients is practically significant for releasing the stress on medical staffs and decreasing the rate of transmission and infection of COVID-19. In this paper, case-based reasoning (CBR) technology is used to assist personalized intervention for chronic diseases, and the key technologies of personalized intervention for chronic diseases based on case-based reasoning are proposed. The case organization, case retrieval, and case retention techniques of CBR technology in chronic disease personalized intervention are designed, and the calculation of interclass dispersion is added to the distribution of feature words, which is used to describe the distribution of feature attributes in different categories of cases. It provides an effective method for the establishment of personalized intervention model for chronic disease.

scholarly journals A Telemedicine Service System Exploiting BT/BLE Wireless Sensors for Remote Management of Chronic Patients

Technologies ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 13 ◽  
Author(s):  
Massimiliano Donati ◽  
Alessio Celli ◽  
Alessio Ruiu ◽  
Sergio Saponara ◽  
Luca Fanucci
Keyword(s):  
Chronic Diseases ◽  
Wireless Sensors ◽  
Clinical Status ◽  
National Health System ◽  
Clinical Information ◽  
Portable Devices ◽  
Chronic Patients ◽  
Telemedicine Service ◽  
Developed Country ◽  
Number Of Patients

The management of the increasing number of patients affected by cardiovascular, pulmonary, and metabolic chronic diseases represents a major challenge for the National Health System (NHS) in any developed country. Chronic diseases are indeed the main cause of hospitalization, especially for elderly people, leading to sustainability problems due to the huge amount of resources required. In the last years, the adoption of the chronic care model (CCM) as assistive model improved the management of these patients and reduced the related healthcare costs. The diffusion of wireless sensors, portable devices and connectivity enables to implement new information and communication technology (ICT)-based innovative applications to further improve the outcomes of the CCM. This paper presents a telemedicine platform for data acquisition, distribution, processing, presentation, and storage, aimed to remotely monitor the clinical status of chronic patients. The proposed solution is based on monitoring kits, with wireless Bluetooth (BT)/ Bluetooth low energy (BLE) sensors and a gateway (i.e., smartphone or tablet) connected to a web-based cloud application that collects and makes available the clinical information to the medical staff. The platform allows clinicians and practitioners to monitor at distance their patients, according to personalized treatment plans, and to act promptly in case of aggravations, reducing hospitalizations and improving patients’ quality of life.

Trend of Case Based Reasoning in Diagnosing Chronic Disease: A Review

2014 ◽  
Vol 20 (10) ◽  
pp. 1740-1744 ◽  
Author(s):  
Daniel Hartono Sutanto ◽  
Nanna Suryana Herman ◽  
Mohd. Khanapi Abd. Ghani
Keyword(s):  
Chronic Disease ◽  
Case Based Reasoning ◽  
Case Based

Research of Case Retrieval Strategy in Case-Based Reasoning

2013 ◽  
Vol 278-280 ◽  
pp. 2016-2019 ◽  
Author(s):  
Jian Hua Song ◽  
Zheng Wang ◽  
Lei Zhang
Keyword(s):  
Case Based Reasoning ◽  
Retrieval Strategy ◽  
Case Retrieval ◽  
Matching Algorithm ◽  
Field Matching ◽  
The Times ◽  
The Impact ◽  
Case Based

This paper put forward a new retrieval strategy which combines character field matching algorithm with the NNH in Case-Based Reasoning. The new retrieval strategy can reduce the times of symptoms match while streamlining retrieved result, and lower the impact of large symptom value difference in the result. The superiority of the strategy is verified by three target cases.

A Case-Based-Reasoning System for Feature Selection and Diagnosing Asthma

2017 ◽  
pp. 444-459
Author(s):  
Somayeh Akhavan Darabi ◽  
Babak Teimourpour
Keyword(s):  
Risk Factors ◽  
Feature Selection ◽  
Chronic Disease ◽  
Early Stage ◽  
Case Based Reasoning ◽  
Asthma Diagnosis ◽  
Stage Of Disease ◽  
Reasoning System ◽  
Therapeutic Measures ◽  
Case Based

Asthma is a chronic disease of the airways in the lungs. The differentiation between asthma, COPD and bronchiectasis in the early stage of disease is very important for the adoption of appropriate therapeutic measures. In this research, a case-based-reasoning (CBR) model is proposed to assist a physician to therapy. First of all, features and symptoms are determined and patients' data is gathered with a questionnaire, then CBR algorithm is run on the data which leads to the asthma diagnosis. The system was tested on 325 asthmatic and non-asthmatic adult cases and the accuracy was eighty percent. The consequences were promising. This study was performed in order to determine risk factors for asthma in a specific society and the results of research showed that the most important variables of asthma disease are symptoms hyper-responsive, frequency of cough and cough.

scholarly journals Syahputra Sistem Pakar Metode Case Based Reasoning Untuk Mengidentifikasi Penyakit Psoriasis

2020 ◽  
Author(s):  
M. Syahputra ◽  
Sarjon Defit ◽  
S Sumijan
Keyword(s):  
Chronic Disease ◽  
Expert System ◽  
Testing System ◽  
Case Based Reasoning ◽  
System Software ◽  
Internal Organs ◽  
Processing Stage ◽  
Life Threatening ◽  
Improving Accuracy ◽  
Case Based

Proriasis is a type of chronic disease of the human skin.problem of psoriasis At the end of the day, theis becoming more interesting because the main cause of this disease has not been found, which has only been found while the cause of psoriasis is genetics. Because the cause is not known for sure, this disease is difficult to cure. Although this disease is not contagious and life-threatening to sufferers, it can damage internal organs if not handled properly. This study aims to determine the level of accuracy in identifying psoriasis in humans. There are several types of symptoms that refer to psoriasis. Furthermore, the data is processed manually with themethod Case Based Reasoning and continued by using a-based expert system software website. The processing stage is to use theprocess, which retrieve is a process of finding the similarities between new cases and existing cases in the knowledge base. The results of the data processing are continued with the calculation of the level of accuracy. The result of testing this method is that there are 100% of the 12 test data. Based on the accuracy of the identification results of this system, this study is very precise in the level of identifying the level of accuracy of psoriasis in humans. Expert testing system has been able to identify thedisease psoriasis specific. Through thismethod Case Based Reasoning , the level of accuracy that can be obtained is quite accurate and can help skin and genital specialists in improving accuracy in identifyingdiseases Case Based Reasoning in humans.

scholarly journals Sistem Pakar Metode Case Based Reasoning untuk Mengidentifikasi Penyakit Psoriasis

2020 ◽  
pp. 20-27
Author(s):  
M Syahputra ◽  
Sarjon Defit ◽  
S Sumijan
Keyword(s):  
Chronic Disease ◽  
Expert System ◽  
Testing System ◽  
Case Based Reasoning ◽  
System Software ◽  
Internal Organs ◽  
Processing Stage ◽  
Life Threatening ◽  
Improving Accuracy ◽  
Case Based

Proriasis is a type of chronic disease of the human skin.problem of psoriasis At the end of the day, theis becoming more interesting because the main cause of this disease has not been found, which has only been found while the cause of psoriasis is genetics. Because the cause is not known for sure, this disease is difficult to cure. Although this disease is not contagious and life-threatening to sufferers, it can damage internal organs if not handled properly. This study aims to determine the level of accuracy in identifying psoriasis in humans. There are several types of symptoms that refer to psoriasis. Furthermore, the data is processed manually with themethod Case Based Reasoning and continued by using a-based expert system software website. The processing stage is to use theprocess, which retrieve is a process of finding the similarities between new cases and existing cases in the knowledge base. The results of the data processing are continued with the calculation of the level of accuracy. The result of testing this method is that there are 100% of the 12 test data. Based on the accuracy of the identification results of this system, this study is very precise in the level of identifying the level of accuracy of psoriasis in humans. Expert testing system has been able to identify thedisease psoriasis specific. Through thismethod Case Based Reasoning , the level of accuracy that can be obtained is quite accurate and can help skin and genital specialists in improving accuracy in identifyingdiseases Case Based Reasoning in humans.

scholarly journals Effects of Private Health Insurance on Unmet Medical Experience in Chronic disease Patients

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J H lee
Keyword(s):  
Health Insurance ◽  
Chronic Disease ◽  
Chronic Diseases ◽  
Low Income ◽  
Private Health Insurance ◽  
Private Insurance ◽  
Median Income ◽  
Chronic Patients ◽  
Medical Experience ◽  
The Impact

Abstract Background Chronic patients are called ’long-term disorders,’ as they last for more than a year. They need continuous care, so health care through easily accessible medical institutions such as primary care is needed for them. In South Korea, however, they are mostly managed through secondary medical service systems, such as hospitals that are difficult to access. This causes them to increase their own burden rate, limiting their ongoing management of the chronic disease. However, it is known that Korea’s private health insurance policy affects the use of medical services, their own burden rate and reduces the unmet medical experience. Therefore this study aims to analyze the impact of the Korean chronic disease on private insurance subscription and unmet medical experience. Methods Using the 2014 survey data of the Korea Welfare Panel, the final analysis of the study was 4,243 households with chronic diseases among 6,581 households. The independent variable of this study is whether private health insurance is subscribed or not, and the dependent variable is unmet medical experience due to economic factors. The analysis method used frequency analysis and logistic regression. [Use SPss 22 for analysis] Results 1,417(33.4%) of households subscribed to private insurance. The figure is significantly lower than the country’s reported private health insurance subscription rate (72.6%). Based on the median income of 60 percent of household income, high-income households have lower unmet medical experience than low-income households. In the case of unsubscribed private health insurance among the people with chronic diseases, the unmet medical experience was 1.921 times higher than that of those who signed up. Conclusions: In order to reduce the burden on chronic patients, the government needs to strengthen the primary medical care system.Reinforce connectivity with private insurance through public financial support of national health insurance. Key messages Chronic disease. Private health insurance.

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