Pub Date : 2023-01-01DOI: 10.5220/0011603400003414
P. Branch, Divya Sridharam, Andre Ferretto, Tim Carroll
{"title":"Fall Prediction Amongst the Elderly Using Data from an Ambient Assisted Living System","authors":"P. Branch, Divya Sridharam, Andre Ferretto, Tim Carroll","doi":"10.5220/0011603400003414","DOIUrl":"https://doi.org/10.5220/0011603400003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"24 1","pages":"218-223"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90746698","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}
Pub Date : 2023-01-01DOI: 10.5220/0011714900003414
Simone Bottoni, Alberto Trombetta, Flavio Bertini, D. Montesi, Francesca Bonin, A. Pascale, Martin Gleize, Pierpaolo Tommasi
{"title":"GASTon: A Graph-Exploration System for Indexing, Annotating and Visualizing PubMed Articles to Enhance the Analysis of Social deTerminants of Health","authors":"Simone Bottoni, Alberto Trombetta, Flavio Bertini, D. Montesi, Francesca Bonin, A. Pascale, Martin Gleize, Pierpaolo Tommasi","doi":"10.5220/0011714900003414","DOIUrl":"https://doi.org/10.5220/0011714900003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"213 1","pages":"424-431"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88651844","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}
Pub Date : 2023-01-01DOI: 10.5220/0011679600003414
A. Campagner, Riccardo Angius, F. Cabitza
: This work contributes to the evaluation of the quality of decision support systems constructed with Machine Learning (ML) techniques in Medical Artificial Intelligence (MAI). In particular, we propose and discuss metrics that complement and go beyond traditional assessment practices based on the evaluation of accuracy, by focusing on two different dimensions related to the trustworthiness of a MAI system: reputation/ability, which relates to the accuracy or predictive ability of the system itself; and expertise/source reliability, which relates instead to the trustworthiness of the data which have been used to construct the MAI system. Then, we will discuss some previous, but so far mostly neglected, proposals as well novel metrics, visualizations and procedures for the sound evaluation of a MAI system’s trustworthiness, by focusing on six different concepts: advice accuracy, advice reliability, pragmatic utility, advice value, decision benefit and potential robustness. Finally, we will illustrate the application of the proposed concepts through two realistic medical case studies.
{"title":"A Question of Trust: Old and New Metrics for the Reliable Assessment of Trustworthy AI","authors":"A. Campagner, Riccardo Angius, F. Cabitza","doi":"10.5220/0011679600003414","DOIUrl":"https://doi.org/10.5220/0011679600003414","url":null,"abstract":": This work contributes to the evaluation of the quality of decision support systems constructed with Machine Learning (ML) techniques in Medical Artificial Intelligence (MAI). In particular, we propose and discuss metrics that complement and go beyond traditional assessment practices based on the evaluation of accuracy, by focusing on two different dimensions related to the trustworthiness of a MAI system: reputation/ability, which relates to the accuracy or predictive ability of the system itself; and expertise/source reliability, which relates instead to the trustworthiness of the data which have been used to construct the MAI system. Then, we will discuss some previous, but so far mostly neglected, proposals as well novel metrics, visualizations and procedures for the sound evaluation of a MAI system’s trustworthiness, by focusing on six different concepts: advice accuracy, advice reliability, pragmatic utility, advice value, decision benefit and potential robustness. Finally, we will illustrate the application of the proposed concepts through two realistic medical case studies.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"42 1","pages":"132-143"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87386352","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}
Pub Date : 2023-01-01DOI: 10.5220/0011925500003414
Ö. Karahan, Yasin Ulukuş, Ç. Erdem
{"title":"A Convolutional Neural Network Model for Prediction of ICU Performance Metrics: Time Series and Image Transformation Approaches","authors":"Ö. Karahan, Yasin Ulukuş, Ç. Erdem","doi":"10.5220/0011925500003414","DOIUrl":"https://doi.org/10.5220/0011925500003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"13 1","pages":"671-679"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85411583","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}
Pub Date : 2023-01-01DOI: 10.5220/0011793800003414
Joep Wegstapel, Thymen den Hartog, Mick Sneekes, Bart Staal, E. V. D. Scheer-Horst, S. Dulmen, S. Brinkkemper
{"title":"Automated Identification of Yellow Flags and Their Signal Terms in Physiotherapeutic Consultation Transcripts","authors":"Joep Wegstapel, Thymen den Hartog, Mick Sneekes, Bart Staal, E. V. D. Scheer-Horst, S. Dulmen, S. Brinkkemper","doi":"10.5220/0011793800003414","DOIUrl":"https://doi.org/10.5220/0011793800003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"152 1","pages":"530-537"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85596583","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}
Pub Date : 2023-01-01DOI: 10.5220/0011800700003414
Nishiki Motokawa, Anna Yokokubo, G. Lopez
{"title":"HydReminder-W: A Bottle Cap that Listens to Your Heart to Remind You to Drink!","authors":"Nishiki Motokawa, Anna Yokokubo, G. Lopez","doi":"10.5220/0011800700003414","DOIUrl":"https://doi.org/10.5220/0011800700003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"43 1","pages":"199-208"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74682595","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}
Pub Date : 2023-01-01DOI: 10.5220/0011780000003414
Nicolás Araya, Javier Gómez, Germán Montoro
{"title":"A Profile Recognition System Based on Emotions for Children with ASD in an Interactive Museum Visit","authors":"Nicolás Araya, Javier Gómez, Germán Montoro","doi":"10.5220/0011780000003414","DOIUrl":"https://doi.org/10.5220/0011780000003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"49 1","pages":"507-513"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79125762","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}
Pub Date : 2023-01-01DOI: 10.5220/0011729100003414
Ayalon Angelo de Moraes Filho, Guilherme Schreiber, Julio Sieg, M. Much, Vanessa Bartoski, C. Marcon
: Academia and industry have devoted significant effort to the research and development of smart wearable devices applied to health monitoring. The photoplethysmography (PPG) sensor is widely used for monitoring biosignals, such as heart and respiratory rate (RR), which are influenced by the cardiovascular system. This work focuses on analyzing methods for RR estimation regarding the effect of breathing on the PPG signal variation. This work describes, implements, and analyzes four methods for estimating RR. These methods are based on capturing RR using Fast Fourier Transform, median, and extracting physiological characteristics induced by respiration in the PPG signal. The most efficient method merges three RR calculations analyzed on the same signal, achieving nearly 93% of efficacy in the best scenario. The method efficacies were calculated using PPG signals from the BIDMC and CapnoBase databases collected from patients during hospital care. The analysis allows for understanding and mitigating the RR estimation challenges and evaluating the most efficacy method for a wearable device monitoring scenario.
{"title":"Methods to Estimate Respiratory Rate Using the Photoplethysmography Signal","authors":"Ayalon Angelo de Moraes Filho, Guilherme Schreiber, Julio Sieg, M. Much, Vanessa Bartoski, C. Marcon","doi":"10.5220/0011729100003414","DOIUrl":"https://doi.org/10.5220/0011729100003414","url":null,"abstract":": Academia and industry have devoted significant effort to the research and development of smart wearable devices applied to health monitoring. The photoplethysmography (PPG) sensor is widely used for monitoring biosignals, such as heart and respiratory rate (RR), which are influenced by the cardiovascular system. This work focuses on analyzing methods for RR estimation regarding the effect of breathing on the PPG signal variation. This work describes, implements, and analyzes four methods for estimating RR. These methods are based on capturing RR using Fast Fourier Transform, median, and extracting physiological characteristics induced by respiration in the PPG signal. The most efficient method merges three RR calculations analyzed on the same signal, achieving nearly 93% of efficacy in the best scenario. The method efficacies were calculated using PPG signals from the BIDMC and CapnoBase databases collected from patients during hospital care. The analysis allows for understanding and mitigating the RR estimation challenges and evaluating the most efficacy method for a wearable device monitoring scenario.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"292 1","pages":"445-452"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79510060","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}
Pub Date : 2023-01-01DOI: 10.5220/0011686900003414
V. M. Anlacan, R. Jamora, A. Panganiban, I. T. O. Salido, Romuel Aloizeus Z. Apuya, Bryan Andrei C. Galecio, M. Tee, M. E. Aguila, C. Tee, J. Caro
{"title":"Analysis of Virtual Reality Therapy Game Prototype for Persons Living with Dementia in the Philippines","authors":"V. M. Anlacan, R. Jamora, A. Panganiban, I. T. O. Salido, Romuel Aloizeus Z. Apuya, Bryan Andrei C. Galecio, M. Tee, M. E. Aguila, C. Tee, J. Caro","doi":"10.5220/0011686900003414","DOIUrl":"https://doi.org/10.5220/0011686900003414","url":null,"abstract":"","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"17 1","pages":"144-154"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75687430","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}
Pub Date : 2023-01-01DOI: 10.5220/0011611000003414
James Kemp, Christopher Barker, Norm M. Good, Michael Bain
: Medical fraud and waste is a costly problem for health insurers. Growing volumes and complexity of data add challenges for detection, which data mining and machine learning may solve. We introduce a framework for incorporating domain knowledge (through the use of the claim ontology), learning claim contexts and provider roles (through topic modelling), and estimating repeated, costly behaviours (by comparison of provider costs to expected costs in each discovered context). When applied to orthopaedic surgery claims, our models highlighted both known and novel patterns of anomalous behaviour. Costly behaviours were ranked highly, which is useful for effective allocation of resources when recovering potentially fraudulent or wasteful claims. Further work on incorporating context discovery and domain knowledge into fraud detection algorithms on medical insurance claim data could improve results in this field.
{"title":"Context Discovery and Cost Prediction for Detection of Anomalous Medical Claims, with Ontology Structure Providing Domain Knowledge","authors":"James Kemp, Christopher Barker, Norm M. Good, Michael Bain","doi":"10.5220/0011611000003414","DOIUrl":"https://doi.org/10.5220/0011611000003414","url":null,"abstract":": Medical fraud and waste is a costly problem for health insurers. Growing volumes and complexity of data add challenges for detection, which data mining and machine learning may solve. We introduce a framework for incorporating domain knowledge (through the use of the claim ontology), learning claim contexts and provider roles (through topic modelling), and estimating repeated, costly behaviours (by comparison of provider costs to expected costs in each discovered context). When applied to orthopaedic surgery claims, our models highlighted both known and novel patterns of anomalous behaviour. Costly behaviours were ranked highly, which is useful for effective allocation of resources when recovering potentially fraudulent or wasteful claims. Further work on incorporating context discovery and domain knowledge into fraud detection algorithms on medical insurance claim data could improve results in this field.","PeriodicalId":20676,"journal":{"name":"Proceedings of the International Conference on Health Informatics and Medical Application Technology","volume":"36 1","pages":"29-40"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77235543","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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