This study aimed to determine whether intuitive play in a real environment affects the cerebral blood flow during the interaction between individuals. We implemented a creativity-related task designed by Cheng and Hashimoto. We focused on using fNIRS technology to investigate the differences between two ways for collaborative problem-solving, namely, do-first and think-first approaches. We obtained significant differences between the activities referring to ideas and the others interpreting concepts. We found that the "do-first" approach facilitates conversations on ideas, which reproduced Cheng and Hashimoto's experiment. We also saw a trend of increased cerebral blood flow in the subjects' prefrontal cortex and increased brain activity when performing the task. Our findings indicate that fNIRS technology enables us to study the mechanism of idea generation.
{"title":"Analysis on mechanisms of idea generation: evidences from fNIRS hyperscanning","authors":"Kecheng Lai, Yuqi Liu, Takehiro Iino, T. Fujinami","doi":"10.1145/3545729.3545765","DOIUrl":"https://doi.org/10.1145/3545729.3545765","url":null,"abstract":"This study aimed to determine whether intuitive play in a real environment affects the cerebral blood flow during the interaction between individuals. We implemented a creativity-related task designed by Cheng and Hashimoto. We focused on using fNIRS technology to investigate the differences between two ways for collaborative problem-solving, namely, do-first and think-first approaches. We obtained significant differences between the activities referring to ideas and the others interpreting concepts. We found that the \"do-first\" approach facilitates conversations on ideas, which reproduced Cheng and Hashimoto's experiment. We also saw a trend of increased cerebral blood flow in the subjects' prefrontal cortex and increased brain activity when performing the task. Our findings indicate that fNIRS technology enables us to study the mechanism of idea generation.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133508320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Azadeh Alizargar, Tan-Hsu Tan, Yang-Lang Chang, Mohammad Alkhaleefah
Hypertension is a common disease which may lead to incurable situation if it is not well-treated. By extracting knowledge from large datasets, data mining can be used for the hypertension prediction and diagnosis. In this research, three data mining techniques, the support vector machine (SVM), k-nearest neighbors (k-NN), and decision tree, were developed to predict the hypertension with two datasets. These techniques were implemented on Google Colab using Python codes. Experimental results illustrate that the accuracy and area under the receiver operating characteristic (ROC) curve performance of all these three techniques on first dataset is 81% and 80.64% for the SVM, 74% and 73.97% for the k-NN, and 74% and 73.86% for the decision tree, respectively. The accuracy and ROC curve performance of these three approaches on the second dataset were 73% and 72.48% for the SVM, 76% and 75.75% for the k-NN model, and 75% and 74.49% for the decision tree, respectively. The results indicate that the SVM, k-NN, and decision tree, are effective in predicting the hypertension based on the obtained important features of the patients, and the k-NN is among the best choice.
{"title":"Hypertension Disease Predictions with Various Models Using Data Science Framework","authors":"Azadeh Alizargar, Tan-Hsu Tan, Yang-Lang Chang, Mohammad Alkhaleefah","doi":"10.1145/3545729.3545751","DOIUrl":"https://doi.org/10.1145/3545729.3545751","url":null,"abstract":"Hypertension is a common disease which may lead to incurable situation if it is not well-treated. By extracting knowledge from large datasets, data mining can be used for the hypertension prediction and diagnosis. In this research, three data mining techniques, the support vector machine (SVM), k-nearest neighbors (k-NN), and decision tree, were developed to predict the hypertension with two datasets. These techniques were implemented on Google Colab using Python codes. Experimental results illustrate that the accuracy and area under the receiver operating characteristic (ROC) curve performance of all these three techniques on first dataset is 81% and 80.64% for the SVM, 74% and 73.97% for the k-NN, and 74% and 73.86% for the decision tree, respectively. The accuracy and ROC curve performance of these three approaches on the second dataset were 73% and 72.48% for the SVM, 76% and 75.75% for the k-NN model, and 75% and 74.49% for the decision tree, respectively. The results indicate that the SVM, k-NN, and decision tree, are effective in predicting the hypertension based on the obtained important features of the patients, and the k-NN is among the best choice.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131884804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jin Li, Jiahui Shao, J. Wu, Jinxia Fang, Tongtong Zhou, Huiqun Wu
With the increasing incidence of retinal fundus disease, more attention has been paid to the screening and prevention of fundus diseases. However, the low efficiency and interoperability issues hinder the application of retinal disease reporting. In this study, we developed an intelligent classification module for retina based on inception V3 pre-trained model. The top rank of eight classification scores was output as recommendation for image reader reviewing, and the other structured report (SR) module was designed to generate FHIR-compliant retinal diagnostic SRs by customizing existing FHIR DiagnosticReport and Observation resources. The results demonstrated the artificial intelligence (AI) classification pop-up window and the validation of produced SR via a public HAPI FHIR server. The results suggested that the SR was easily shared and could be accurately and integrated with other hospitals or clinical research institutions. In summary, our developed AI assisted SRs module is clinical workflow friendly, and the produced SRs could be easily shared and integrated, which can provide a meaningful use way for further analytic research.
{"title":"The development and implementation of deep learning assisted interoperable retinal image structured report module in PACS","authors":"Jin Li, Jiahui Shao, J. Wu, Jinxia Fang, Tongtong Zhou, Huiqun Wu","doi":"10.1145/3545729.3545753","DOIUrl":"https://doi.org/10.1145/3545729.3545753","url":null,"abstract":"With the increasing incidence of retinal fundus disease, more attention has been paid to the screening and prevention of fundus diseases. However, the low efficiency and interoperability issues hinder the application of retinal disease reporting. In this study, we developed an intelligent classification module for retina based on inception V3 pre-trained model. The top rank of eight classification scores was output as recommendation for image reader reviewing, and the other structured report (SR) module was designed to generate FHIR-compliant retinal diagnostic SRs by customizing existing FHIR DiagnosticReport and Observation resources. The results demonstrated the artificial intelligence (AI) classification pop-up window and the validation of produced SR via a public HAPI FHIR server. The results suggested that the SR was easily shared and could be accurately and integrated with other hospitals or clinical research institutions. In summary, our developed AI assisted SRs module is clinical workflow friendly, and the produced SRs could be easily shared and integrated, which can provide a meaningful use way for further analytic research.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"50 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123692169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Vichova, M. Hromada, Frantisek Paulus, J. Valasek
Disruption of the critical infrastructure element can seriously impact the security of the state, the necessities of the population, and the state's economy. One essential element of infrastructure is healthcare. Due to the large concentration of inhabitants, the healthcare system can target terrorist attacks. These attacks may be by chemical, biological, radiological, and nuclear (CBRN) weapons. The aim of the paper is to assess the hospital's preparedness to solve terrorist attacks. Secondly, the case study for the selected hospital in the Czech Republic was prepared. Heuristic preparedness analysis and TerEx software were selected for the preparing results. Based on the analytical method, we get an idea of the preparedness system to solve terrorist attacks in hospitals and vulnerabilities. TerEx software is used for the mathematical model of the case study. The preparedness of individual hospitals varies in the Czech Republic. Therefore, it is essential that hospitals, as elements of critical infrastructure, reduce the risk of terrorist attacks using CBRN weapons.
{"title":"CBRN Weapons as a Threat to Critical Infrastructure Elements","authors":"K. Vichova, M. Hromada, Frantisek Paulus, J. Valasek","doi":"10.1145/3545729.3545780","DOIUrl":"https://doi.org/10.1145/3545729.3545780","url":null,"abstract":"Disruption of the critical infrastructure element can seriously impact the security of the state, the necessities of the population, and the state's economy. One essential element of infrastructure is healthcare. Due to the large concentration of inhabitants, the healthcare system can target terrorist attacks. These attacks may be by chemical, biological, radiological, and nuclear (CBRN) weapons. The aim of the paper is to assess the hospital's preparedness to solve terrorist attacks. Secondly, the case study for the selected hospital in the Czech Republic was prepared. Heuristic preparedness analysis and TerEx software were selected for the preparing results. Based on the analytical method, we get an idea of the preparedness system to solve terrorist attacks in hospitals and vulnerabilities. TerEx software is used for the mathematical model of the case study. The preparedness of individual hospitals varies in the Czech Republic. Therefore, it is essential that hospitals, as elements of critical infrastructure, reduce the risk of terrorist attacks using CBRN weapons.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"11 12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124619964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sabah Mohammed, J. Fiaidhi, Darien Sawyer, Mehdi Lamouchie
Healthcare institutions are slowly starting to deploy chatbots as a new method of communication with their patients. However, most of the automated chatbots fails to satisfy the patient expectation. Moreover, the idea of simulating a conversation similar to how the physician-patient interact when a patient encounter a health issue is not fully understood and implemented. Due to the infancy and lack of research on building such conversational chatbots that can work together to seek information and to answer queries related to a patient encounter and record it using a clinical charting format like SOAP, the purpose of this paper is to describe our attempt and the architecture that we build using the AWS AppSync which has been integrated with our QL4POMR medical record system. We are attempting to use the prototype to learn the limitations regarding it usability at different clinical practices. Additional constructs or artificial intelligence techniques could be used to obtain higher acceptability and to fit specific clinical practices.
{"title":"Developing a GraphQL SOAP Conversational Micro Frontends for the Problem Oriented Medical Record (QL4POMR)","authors":"Sabah Mohammed, J. Fiaidhi, Darien Sawyer, Mehdi Lamouchie","doi":"10.1145/3545729.3545738","DOIUrl":"https://doi.org/10.1145/3545729.3545738","url":null,"abstract":"Healthcare institutions are slowly starting to deploy chatbots as a new method of communication with their patients. However, most of the automated chatbots fails to satisfy the patient expectation. Moreover, the idea of simulating a conversation similar to how the physician-patient interact when a patient encounter a health issue is not fully understood and implemented. Due to the infancy and lack of research on building such conversational chatbots that can work together to seek information and to answer queries related to a patient encounter and record it using a clinical charting format like SOAP, the purpose of this paper is to describe our attempt and the architecture that we build using the AWS AppSync which has been integrated with our QL4POMR medical record system. We are attempting to use the prototype to learn the limitations regarding it usability at different clinical practices. Additional constructs or artificial intelligence techniques could be used to obtain higher acceptability and to fit specific clinical practices.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125355525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Citizens are people who have a high risk of exposure to diseases due to unhealthy environmental conditions. This requires citizens to take advantage of health services in order to get optimal examinations. The purpose of this study was to determine the description and relationship between the characteristics of citizens and the utilization of health services by citizens in the area of Indonesia in 2020. The quantitative research method with cross- sectional design used random sampling techniques. The number of samples was 150 families in the area of Tangerang Selatan, Indonesia. Measuring instrument in the form of a questionnaire with data collection techniques in the interviews form. Data analysis used chi-square analysis and multiple logistic regression analysis. The results showed that the variables related to the utilization of health services were knowledge variable (p = 0.001), number of families (p = 0.021), perception of pain (p = 0.001), and family support (p = 0.030). And the variables that were not related to the utilization of health services were ownership of health insurance (p = 0.750), transportation (p = 0.297). As well as the dominant variable related to the utilization of health services, that is knowledge (p = 0.000) with OR 12.876. It is hope that prima Wry health care and health workers can involve more communities around the area in their work programs, such as providing health information.
{"title":"The Relationship between The Characteristics of Citizens and Healthcare with The Utilization Of Health Services in Indonesia","authors":"P. Permatasari, Cahya Arbitera, Dwi Mutia Wenny","doi":"10.1145/3545729.3545787","DOIUrl":"https://doi.org/10.1145/3545729.3545787","url":null,"abstract":"Citizens are people who have a high risk of exposure to diseases due to unhealthy environmental conditions. This requires citizens to take advantage of health services in order to get optimal examinations. The purpose of this study was to determine the description and relationship between the characteristics of citizens and the utilization of health services by citizens in the area of Indonesia in 2020. The quantitative research method with cross- sectional design used random sampling techniques. The number of samples was 150 families in the area of Tangerang Selatan, Indonesia. Measuring instrument in the form of a questionnaire with data collection techniques in the interviews form. Data analysis used chi-square analysis and multiple logistic regression analysis. The results showed that the variables related to the utilization of health services were knowledge variable (p = 0.001), number of families (p = 0.021), perception of pain (p = 0.001), and family support (p = 0.030). And the variables that were not related to the utilization of health services were ownership of health insurance (p = 0.750), transportation (p = 0.297). As well as the dominant variable related to the utilization of health services, that is knowledge (p = 0.000) with OR 12.876. It is hope that prima Wry health care and health workers can involve more communities around the area in their work programs, such as providing health information.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116695849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this study is to develop a model for tracking and monitoring medical records in hospitals with limited database and computing resources. Electronic health records were collected from regional hospitals in Thailand with prescribing guidelines from the national public health administration, as health care management is complicated by a wide range of drug options and a wide range of health benefit options. The cost of treatment for patients with chronic diseases was also significantly higher than for patients with other diseases, according to the regression analysis. Patients with universal coverage plans have seen lower healthcare costs as a result of regulations and differentiation in the service of multiple health benefit programs.
{"title":"Choice variation on electronic health database: a case study of medical decision mapping from healthcare scheme of Thailand","authors":"P. Tansitpong","doi":"10.1145/3545729.3545749","DOIUrl":"https://doi.org/10.1145/3545729.3545749","url":null,"abstract":"The goal of this study is to develop a model for tracking and monitoring medical records in hospitals with limited database and computing resources. Electronic health records were collected from regional hospitals in Thailand with prescribing guidelines from the national public health administration, as health care management is complicated by a wide range of drug options and a wide range of health benefit options. The cost of treatment for patients with chronic diseases was also significantly higher than for patients with other diseases, according to the regression analysis. Patients with universal coverage plans have seen lower healthcare costs as a result of regulations and differentiation in the service of multiple health benefit programs.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"290 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131520774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Radiomics is a new and emerging field that leverages advancements in machine learning and computational capabilities to provide prognostic and diagnostic outcomes. Using standard medical imaging techniques used to assess the location and spread of the tumor, radiomics is used to compute a wealth of information using sub-visual features from existing images to identify cancer biomarkers. This paper explores the various applications of radiomics, specifically in head and neck cancer imaging. We provide a detailed radiomics workflow for medical image data. We identify the various applications and highlight relevant research works in these applications. We address the challenges faced in the field and highlight future work in this area. This work is helpful to those researchers interested in interdisciplinary research focused on image processing in the Head and Neck anatomy.
{"title":"Using Machine Learning for Precision Prognostics in Head and Neck Cancer Images","authors":"D. Rao, Prakashini, Rohit Singh, Vijayananda","doi":"10.1145/3545729.3545734","DOIUrl":"https://doi.org/10.1145/3545729.3545734","url":null,"abstract":"Radiomics is a new and emerging field that leverages advancements in machine learning and computational capabilities to provide prognostic and diagnostic outcomes. Using standard medical imaging techniques used to assess the location and spread of the tumor, radiomics is used to compute a wealth of information using sub-visual features from existing images to identify cancer biomarkers. This paper explores the various applications of radiomics, specifically in head and neck cancer imaging. We provide a detailed radiomics workflow for medical image data. We identify the various applications and highlight relevant research works in these applications. We address the challenges faced in the field and highlight future work in this area. This work is helpful to those researchers interested in interdisciplinary research focused on image processing in the Head and Neck anatomy.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132659587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tim Moesgen, Antti Salovaara, Emmi Pouta, Rebecka Pyykko, Yu Xiao
Stroke is one of the most common causes of death globally and a reason for severe impairments. Many stroke survivors report a loss of muscle strength and, thus, need to regain motor control of their upper limbs with rehabilitation. In some cases, patients may compensate for muscle weakness with harmful compensatory movements using other muscles. We envision that VR-based training can provide multimodal feedback during sensorimotor training to avoid compensatory movements. However, feedback may be hampered by changes in patients’ somatosensory system, resulting in both weakened and intensified tactile perceptions. We explored the differences in perception of vibration metaphors for motion guidance between healthy participants and stroke patients and assessed the efficiency of multimodal feedback for the correction of arm trajectory. Multimodal stimuli for trajectory correction benefited the patients but there were also differences in their tactile perception. These patient-specific findings call for the involvement of patients in the design process of haptic rehabilitation devices, following the recommendations of patient-centric healthcare.
{"title":"Vibrotactile Motion Guidance for Stroke Rehabilitation: A Comparative Study","authors":"Tim Moesgen, Antti Salovaara, Emmi Pouta, Rebecka Pyykko, Yu Xiao","doi":"10.1145/3545729.3545759","DOIUrl":"https://doi.org/10.1145/3545729.3545759","url":null,"abstract":"Stroke is one of the most common causes of death globally and a reason for severe impairments. Many stroke survivors report a loss of muscle strength and, thus, need to regain motor control of their upper limbs with rehabilitation. In some cases, patients may compensate for muscle weakness with harmful compensatory movements using other muscles. We envision that VR-based training can provide multimodal feedback during sensorimotor training to avoid compensatory movements. However, feedback may be hampered by changes in patients’ somatosensory system, resulting in both weakened and intensified tactile perceptions. We explored the differences in perception of vibration metaphors for motion guidance between healthy participants and stroke patients and assessed the efficiency of multimodal feedback for the correction of arm trajectory. Multimodal stimuli for trajectory correction benefited the patients but there were also differences in their tactile perception. These patient-specific findings call for the involvement of patients in the design process of haptic rehabilitation devices, following the recommendations of patient-centric healthcare.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121760812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chronic Kidney Disease (CKD) is a condition where kidneys partially work in filtering waste products from blood. In most cases, CKD patients do not experience any symptoms in the early stages. This makes early detection of CKD much harder. The result is starting treatment at a later stage which not only complicates the health condition of the patient, but it also increases the healthcare cost for the patient. This paper describes a mobile application the authors have developed which can be used by any healthcare practitioner. In addition to detecting the presence and the stage of CKD, the application also lets the user find out two risk factors associated with CKD patients, namely Anemia and Mineral Bone Disease (MBD). After detecting either or both of these risk factors, the tool recommends initial treatment plans for the same based on guidelines provided the National Kidney Foundation (NKF) in the United States.
{"title":"A Mobile Application for Chronic Kidney Disease (CKD) Diagnosis","authors":"K. Periyasamy, A. Kaivelikkal, V. Iyer","doi":"10.1145/3545729.3545740","DOIUrl":"https://doi.org/10.1145/3545729.3545740","url":null,"abstract":"Chronic Kidney Disease (CKD) is a condition where kidneys partially work in filtering waste products from blood. In most cases, CKD patients do not experience any symptoms in the early stages. This makes early detection of CKD much harder. The result is starting treatment at a later stage which not only complicates the health condition of the patient, but it also increases the healthcare cost for the patient. This paper describes a mobile application the authors have developed which can be used by any healthcare practitioner. In addition to detecting the presence and the stage of CKD, the application also lets the user find out two risk factors associated with CKD patients, namely Anemia and Mineral Bone Disease (MBD). After detecting either or both of these risk factors, the tool recommends initial treatment plans for the same based on guidelines provided the National Kidney Foundation (NKF) in the United States.","PeriodicalId":432782,"journal":{"name":"Proceedings of the 6th International Conference on Medical and Health Informatics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127006892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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