2018
Neves, J.; Vicente, H.; Esteves, M.; Ferraz, F.; Abelha, A.; Machado, J.; Machado, J.; Neves, J.
Waiting time screening in healthcare Proceedings Article
Em: K.N., Jung J. J. Kim P. Choi (Ed.): pp. 124-131, Springer Verlag, 2018, ISSN: 18678211, (cited By 1; Conference of 8th International Conference on Big Data Technologies and Applications, BDTA 2017 ; Conference Date: 23 November 2017 Through 24 November 2017; Conference Code:220889).
Resumo | Links | BibTeX | Etiquetas: Asymptomatic patients; Human bodies; Laboratory testing; Medical treatment; Operational data; Type of technology; Various technologies; Waiting-time, Big data; Case based reasoning; Computerized tomography; Decision support systems; Health care; Logic programming; Magnetic resonance; Medical imaging, Diagnosis
@inproceedings{Neves2018124,
title = {Waiting time screening in healthcare},
author = {J. Neves and H. Vicente and M. Esteves and F. Ferraz and A. Abelha and J. Machado and J. Machado and J. Neves},
editor = {Jung J. J. Kim P. Choi K.N.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057187471&doi=10.1007%2f978-3-319-98752-1_14&partnerID=40&md5=ff8c5917c0a23f21c5d0c79c6e4173b3},
doi = {10.1007/978-3-319-98752-1_14},
issn = {18678211},
year = {2018},
date = {2018-01-01},
journal = {Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST},
volume = {248},
pages = {124-131},
publisher = {Springer Verlag},
abstract = {In Medical Imaging (MI), various technologies can be used to monitor the human body for diagnosing, monitoring or treating disease. Each type of technology provides different information about the body area that is being investigated or treated for a possible illness, injury or effectiveness of a medical treatment. Routine screening has identified malfunction detection in many otherwise asymptomatic patient images such as computed tomography or magnetic resonance. Studies have shown that, compared to patients whose disease was symptomatic (i.e., self-recognizing), screen-detected diseases may have more favorable clinicopathological features, leading to better prognosis and better outcome. This paper aims to assess the issue of health care wait screening. It deviates from a decision support system that evaluates the waiting times in diagnostic MI based on operational data from various information systems. Last but not least, one’s assumptions may have an important impact in determining the usefulness of routine laboratory testing at admission. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.},
note = {cited By 1; Conference of 8th International Conference on Big Data Technologies and Applications, BDTA 2017 ; Conference Date: 23 November 2017 Through 24 November 2017; Conference Code:220889},
keywords = {Asymptomatic patients; Human bodies; Laboratory testing; Medical treatment; Operational data; Type of technology; Various technologies; Waiting-time, Big data; Case based reasoning; Computerized tomography; Decision support systems; Health care; Logic programming; Magnetic resonance; Medical imaging, Diagnosis},
pubstate = {published},
tppubtype = {inproceedings}
}
In Medical Imaging (MI), various technologies can be used to monitor the human body for diagnosing, monitoring or treating disease. Each type of technology provides different information about the body area that is being investigated or treated for a possible illness, injury or effectiveness of a medical treatment. Routine screening has identified malfunction detection in many otherwise asymptomatic patient images such as computed tomography or magnetic resonance. Studies have shown that, compared to patients whose disease was symptomatic (i.e., self-recognizing), screen-detected diseases may have more favorable clinicopathological features, leading to better prognosis and better outcome. This paper aims to assess the issue of health care wait screening. It deviates from a decision support system that evaluates the waiting times in diagnostic MI based on operational data from various information systems. Last but not least, one’s assumptions may have an important impact in determining the usefulness of routine laboratory testing at admission. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2018.
2015
Neves, J.; Cunha, A.; Almeida, A.; Carvalho, A.; Neves, J.; Abelha, A.; Machado, J.; Vicente, H.
Artificial neural networks in diagnosis of liver diseases Proceedings Article
Em: M., Khuri S. Holzinger A. Elena Renda (Ed.): pp. 71-80, Springer Verlag, 2015, ISSN: 03029743, (cited By 5; Conference of 6th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2015 ; Conference Date: 3 September 2015 Through 4 September 2015; Conference Code:139329).
Resumo | Links | BibTeX | Etiquetas: Artificial neuronal network; Diagnosis support systems; Early diagnosis; Formal framework; Knowledge representation and reasoning; Liver disease; Premature death, Computation theory; Health care; Information science; Knowledge representation; Logic programming; Neural networks; Neurons; Program diagnostics, Diagnosis
@inproceedings{Neves201571,
title = {Artificial neural networks in diagnosis of liver diseases},
author = {J. Neves and A. Cunha and A. Almeida and A. Carvalho and J. Neves and A. Abelha and J. Machado and H. Vicente},
editor = {Khuri S. Holzinger A. Elena Renda M.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84943624859&doi=10.1007%2f978-3-319-22741-2_7&partnerID=40&md5=828f2d651a066de63ed81f6d70e92325},
doi = {10.1007/978-3-319-22741-2_7},
issn = {03029743},
year = {2015},
date = {2015-01-01},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
volume = {9267},
pages = {71-80},
publisher = {Springer Verlag},
abstract = {Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks. © Springer International Publishing Switzerland 2015.},
note = {cited By 5; Conference of 6th International Conference on Information Technology in Bio- and Medical Informatics, ITBAM 2015 ; Conference Date: 3 September 2015 Through 4 September 2015; Conference Code:139329},
keywords = {Artificial neuronal network; Diagnosis support systems; Early diagnosis; Formal framework; Knowledge representation and reasoning; Liver disease; Premature death, Computation theory; Health care; Information science; Knowledge representation; Logic programming; Neural networks; Neurons; Program diagnostics, Diagnosis},
pubstate = {published},
tppubtype = {inproceedings}
}
Liver diseases have severe patients’ consequences, being one of the main causes of premature death. These facts reveal the centrality of one`s daily habits, and how important it is the early diagnosis of these kind of illnesses, not only to the patients themselves, but also to the society in general. Therefore, this work will focus on the development of a diagnosis support system to these kind of maladies, built under a formal framework based on Logic Programming, in terms of its knowledge representation and reasoning procedures, complemented with an approach to computing grounded on Artificial Neural Networks. © Springer International Publishing Switzerland 2015.
Neves, J.; Martins, M. Rosário; Vicente, H.; Neves, J.; Abelha, A.; Machado, J.
An assessment of chronic kidney diseases Proceedings Article
Em: A., Correia A. M. Rocha A. Rocha (Ed.): pp. 179-191, Springer Verlag, 2015, ISSN: 21945357, (cited By 2; Conference of World Conference on Information Systems and Technologies, WorldCIST 2015 ; Conference Date: 1 April 2015 Through 3 April 2015; Conference Code:115919).
Resumo | Links | BibTeX | Etiquetas: Artificial neuronal network; Chronic kidney disease; Glomerular filtration rate; Kidney dysfunction; Kidney function; Knowledge representation and reasoning; Mechanism of injury; Urinary sediment, Diagnosis, Health care; Information systems; Knowledge representation; Logic programming; Neurons
@inproceedings{Neves2015179,
title = {An assessment of chronic kidney diseases},
author = {J. Neves and M. Rosário Martins and H. Vicente and J. Neves and A. Abelha and J. Machado},
editor = {Correia A. M. Rocha A. Rocha A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84926295620&doi=10.1007%2f978-3-319-16486-1_18&partnerID=40&md5=ed38e161692c5017fd25d6a9f5d92586},
doi = {10.1007/978-3-319-16486-1_18},
issn = {21945357},
year = {2015},
date = {2015-01-01},
journal = {Advances in Intelligent Systems and Computing},
volume = {353},
pages = {179-191},
publisher = {Springer Verlag},
abstract = {Once kidney disease is exposed, the presence or degree of kidney dysfunction and its progression are assessed, and the underlying syndrome may be diagnosed. Although the patient`s history and corporeal examination may be useful, some key information is obtained from valuation of the Glomerular Filtration Rate, and analysis of the urinary sediment. On the one hand, Chronic Kidney Diseases (CKDs) depicts anomalous kidney function and/or its makeup. On the other hand, there is evidence that treatment may avoid or delay the progression of CKDs, either by reducing and prevent the development of complications, or by reducing the risk of CardioVascular Illnesses. Acute Renal Failure (ARF) can occur over hours to days based on the underlying mechanism of injury and relative health of the individual. ARF is often reversible if it is recognized early and treated promptly. This is the reason behind our compromise in presenting this work, that aims at the development of an early diagnosis system to monitor the occurrence of the disease, and therefore to allow one to act proactively. © Springer International Publishing Switzerland 2015.},
note = {cited By 2; Conference of World Conference on Information Systems and Technologies, WorldCIST 2015 ; Conference Date: 1 April 2015 Through 3 April 2015; Conference Code:115919},
keywords = {Artificial neuronal network; Chronic kidney disease; Glomerular filtration rate; Kidney dysfunction; Kidney function; Knowledge representation and reasoning; Mechanism of injury; Urinary sediment, Diagnosis, Health care; Information systems; Knowledge representation; Logic programming; Neurons},
pubstate = {published},
tppubtype = {inproceedings}
}
Once kidney disease is exposed, the presence or degree of kidney dysfunction and its progression are assessed, and the underlying syndrome may be diagnosed. Although the patient`s history and corporeal examination may be useful, some key information is obtained from valuation of the Glomerular Filtration Rate, and analysis of the urinary sediment. On the one hand, Chronic Kidney Diseases (CKDs) depicts anomalous kidney function and/or its makeup. On the other hand, there is evidence that treatment may avoid or delay the progression of CKDs, either by reducing and prevent the development of complications, or by reducing the risk of CardioVascular Illnesses. Acute Renal Failure (ARF) can occur over hours to days based on the underlying mechanism of injury and relative health of the individual. ARF is often reversible if it is recognized early and treated promptly. This is the reason behind our compromise in presenting this work, that aims at the development of an early diagnosis system to monitor the occurrence of the disease, and therefore to allow one to act proactively. © Springer International Publishing Switzerland 2015.