International Journal of Biomedical Engineering and Technology http://www.inderscience.com/browse/index.php?journalID=226&year=2012&vol=8&issue=1 Inderscience Publishers Ltd en-uk International Journal of Biomedical Engineering and Technology 1752-6418 1752-6426 © 2012 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijbet_scoverijbet.jpg http://www.inderscience.com/browse/index.php?journalID=226&year=2012&vol=8&issue=1 http://www.inderscience.com/link.php?id=45354 Population-based screening has been accepted as the best tool for preventing breast cancer. Many women cohorts are left out from screening sessions on a regular basis. Increasing screening attendance through well-coordinated interventions has been accepted as a norm for such screening programme. The need for more resources for making such interventions within the primary care domain has held back many such initiatives. A case study on increasing screening attendance through prediction techniques to identify women likely to miss screening and initiate opportunistic intervention, is discussed in this paper. A new intervention research framework and a questionnaire-based survey are also presented. Information technology-initiated interventions: a case study for the UK National Health Service Breast Screening Programme to improve screening attendance using a new intervention research framework
V. Baskaran; A. Guergachi; B. Shah; S. Sidani; R.K. Bali; R.N.G. Naguib; N. Wickramasinghe
International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 1 - 17
Population-based screening has been accepted as the best tool for preventing breast cancer. Many women cohorts are left out from screening sessions on a regular basis. Increasing screening attendance through well-coordinated interventions has been accepted as a norm for such screening programme. The need for more resources for making such interventions within the primary care domain has held back many such initiatives. A case study on increasing screening attendance through prediction techniques to identify women likely to miss screening and initiate opportunistic intervention, is discussed in this paper. A new intervention research framework and a questionnaire-based survey are also presented.

]]> 10.1504/IJBET.2012.045354 International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 1 - 17 V. Baskaran; A. Guergachi; B. Shah; S. Sidani; R.K. Bali; R.N.G. Naguib; N. Wickramasinghe Ted Rogers School of Information Technology Management, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B 2K3, Canada. ' Ted Rogers School of Information Technology Management, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B 2K3, Canada. ' Ted Rogers School of Information Technology Management, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B 2K3, Canada. ' School of Nursing, Ryerson University, 350 Victoria Street, Toronto, Ontario M5B 2K3, Canada. ' Biomedical Computing and Engineering Technologies (BIOCORE) Applied Research Group, Health Design and Technology Institute (HDTI), Coventry University, Coventry University Technology Park, Puma Way, Coventry CV1 2TT, UK. ' Biomedical Computing and Engineering Technologies (BIOCORE) Applied Research Group, Health Design and Technology Institute (HDTI), Coventry University, Coventry University Technology Park, Puma Way, Coventry CV1 2TT, UK. ' Epworth Chair Health Information Management, Business IT & Logistics, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia breast screening opportunistic intervention screening attendance prediction primary care breast cancer prevention UK NHS National Health Service United Kingdom increasing attendance information technology healthcare technology. 2012-02-06T23:20:50-05:00 8 1 1 17 2012-02-06T23:20:50-05:00 http://www.inderscience.com/link.php?id=45355 Survival in choroidal melanoma was modelled using accelerated failure time models. We combined pathological, clinical and genetic data, using imputation techniques. Performance was assessed using n-fold cross-validation. Using data from 3653 patients, we generated two models; the first using clinical data only and the second using clinical and laboratory data. The c-index of discrimination was 0.75 for the clinical model and 0.79 for the laboratory model. Calibration showed good correlation between predicted and observed mortality (p-value: 0.699 for clinical model and 0.801 for laboratory model). We conclude that our model provides reasonably reliable prognosis relevant to individual patients. Enhancing survival prognostication in patients with choroidal melanoma by integrating pathologic, clinical and genetic predictors of metastasis
Antonio Eleuteri; Bertil Damato; Sarah E. Coupland; Azzam F.G. Taktak
International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 18 - 35
Survival in choroidal melanoma was modelled using accelerated failure time models. We combined pathological, clinical and genetic data, using imputation techniques. Performance was assessed using n-fold cross-validation. Using data from 3653 patients, we generated two models; the first using clinical data only and the second using clinical and laboratory data. The c-index of discrimination was 0.75 for the clinical model and 0.79 for the laboratory model. Calibration showed good correlation between predicted and observed mortality (p-value: 0.699 for clinical model and 0.801 for laboratory model). We conclude that our model provides reasonably reliable prognosis relevant to individual patients.

]]> 10.1504/IJBET.2012.045355 International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 18 - 35 Antonio Eleuteri; Bertil Damato; Sarah E. Coupland; Azzam F.G. Taktak Department of Medical Physics and Clinical Engineering, Royal Liverpool University Hospital, Duncan Building, Daulby St., Liverpool L7 8XP, UK. ' Ocular Oncology Service, Royal Liverpool University Hospital, Prescot St., Liverpool, L7 8XP, UK. ' Department of Molecular and Clinical Cancer Medicine, University of Liverpool, Duncan Building, Daulby Street, Liverpool, L69 3GA, UK. ' Department of Medical Physics and Clinical Engineering, Royal Liverpool University Hospital, 1st Floor, Duncan Building, Daulby St., Liverpool L7 8XP, UK uveal melanoma mortality chromosome aberrations prognostication histology mathematical modelling choroidal melanoma pathological predictors clinical predictors genetic predictors patient survival. 2012-02-06T23:20:50-05:00 8 1 18 35 2012-02-06T23:20:50-05:00 http://www.inderscience.com/link.php?id=45356 Myocardial ischaemia is the detection of ischaemic episodes in the Electrocardiogram (ECG) recordings can be very supportive to the physicians, relies heavily on the relevant and efficient feature extraction and classification of the ST segment. In this paper, the Genetic Algorithm (GA) and fuzzy logic is combined with PCA and ICA to improve their performance; the algorithms are Fuzzy-Genetic PCA (FGPCA) and Fuzzy-Genetic ICA (FGICA). In the proposed method, the features are classified using a Genetic-based Least Square Support Vector Machine (GLSSVM). The results demonstrated that the GLSSVM with FGICA achieved greater accuracy higher than the other automated diagnostic systems. Automatic ischaemic beats classification using Genetic-based Least Square Support Vector Machine
S. Murugan; S. Radhakrishnan
International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 36 - 48
Myocardial ischaemia is the detection of ischaemic episodes in the Electrocardiogram (ECG) recordings can be very supportive to the physicians, relies heavily on the relevant and efficient feature extraction and classification of the ST segment. In this paper, the Genetic Algorithm (GA) and fuzzy logic is combined with PCA and ICA to improve their performance; the algorithms are Fuzzy-Genetic PCA (FGPCA) and Fuzzy-Genetic ICA (FGICA). In the proposed method, the features are classified using a Genetic-based Least Square Support Vector Machine (GLSSVM). The results demonstrated that the GLSSVM with FGICA achieved greater accuracy higher than the other automated diagnostic systems.

]]> 10.1504/IJBET.2012.045356 International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 36 - 48 S. Murugan; S. Radhakrishnan Department of ICE, Arulmigu Kalasalingam College of Engineering, Krishnankoil 626190, Srivilliputhur, Tamil Nadu, India. ' Department of ICE, Arulmigu Kalasalingam College of Engineering, Krishnankoil 626190, Srivilliputhur, Tamil Nadu, India myocardial ischaemia GAs genetic algorithms classification ischaemic beats least squares SVM support vector machines electrocardiograms ECG fuzzy logic automated diagnosis heartbeats cardic problems cardiovascular disease heart rate feature extraction PCA principal component analysis ICA independent component analysis. 2012-02-06T23:20:50-05:00 8 1 36 48 2012-02-06T23:20:50-05:00 http://www.inderscience.com/link.php?id=45357 Receiver Operating Characteristics (ROC) analysis is commonly used in medical decision making, and in recent years has been used increasingly in machine learning and data-mining research. In this study, it is used for assessing the performance of classification algorithms in predicting trauma patients outcome. Data set comprised 8544 severely injured patients who had been admitted to Hellenic hospitals from the year 2005 to 2006. We analysed the demographic data and the factors that may have influenced the outcome in the group of patients with trauma and several combinations of significant factors were determined for that purpose. Classification methods and ROC analysis for outcome prediction of patients following injuries
C. Koukouvinos; C. Parpoula; E.-M. Theodoraki
International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 49 - 59
Receiver Operating Characteristics (ROC) analysis is commonly used in medical decision making, and in recent years has been used increasingly in machine learning and data-mining research. In this study, it is used for assessing the performance of classification algorithms in predicting trauma patients outcome. Data set comprised 8544 severely injured patients who had been admitted to Hellenic hospitals from the year 2005 to 2006. We analysed the demographic data and the factors that may have influenced the outcome in the group of patients with trauma and several combinations of significant factors were determined for that purpose.

]]> 10.1504/IJBET.2012.045357 International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 49 - 59 C. Koukouvinos; C. Parpoula; E.-M. Theodoraki Department of Mathematics, National Technical University of Athens, Zografou 15773, Athens, Greece. ' Department of Mathematics, National Technical University of Athens, Zografou 15773, Athens, Greece. ' Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, Karlovassi 83200, Samos Island, Greece data mining classi?cation trees ROC analysis medical data outcome prediction receiver operating characteristics medical decision making trauma patients patient outcomes severe injuries Greece. 2012-02-06T23:20:50-05:00 8 1 49 59 2012-02-06T23:20:50-05:00 http://www.inderscience.com/link.php?id=45358 A proof-of principle prototype of a non-invasive blood glucose monitor based on impedance measurements was developed and tested, with the average error between invasive glucose readings and non-invasive estimate less than 20% for type 1, type 2 and healthy users and for static and dynamic tests. Discussed are the schematics of the device, data acquisition and filtering, and data processing, with the emphasis on Neural Network (NN) algorithms. Development of a non-invasive blood glucose monitor based on impedance measurements
Len Malinin
International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 60 - 81
A proof-of principle prototype of a non-invasive blood glucose monitor based on impedance measurements was developed and tested, with the average error between invasive glucose readings and non-invasive estimate less than 20% for type 1, type 2 and healthy users and for static and dynamic tests. Discussed are the schematics of the device, data acquisition and filtering, and data processing, with the emphasis on Neural Network (NN) algorithms.

]]> 10.1504/IJBET.2012.045358 International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 60 - 81 Len Malinin GEN3 Partners, 20 Winthrop Square, Second Floor, Boston, MA 02110, USA non-invasive monitoring blood glucose monitoring impedance measurements specificity calibration ANNs artificial neural networks diabetes biomedical technology wearable devices medical devices. 2012-02-06T23:20:50-05:00 8 1 60 81 2012-02-06T23:20:50-05:00 http://www.inderscience.com/link.php?id=45359 The concept of Superharmonic Imaging (SHI) evolved because of non-linear propagation of ultrasound in biological. In this work, the comparison of fundamental, second and superharmonic components are presented, which is associated with amplitude and propagation distance along on-axis and off-axis as well. The parameters associated with imaging quality are: lateral and axial resolutions; depth of field and Signal to Noise Ratio (SNR). The trade-offs among above-mentioned four aspects of fundamental, second harmonic and superharmonic fields and relating them to system parameters such as aperture size, f-number, focal depth, central frequency and applied pressure help in superharmonic beam optimisation, which further enhances imaging ability. Numerical investigation of non-linear propagation of amplitude-modulated ultrasound pulses in human soft tissues and superharmonic beam optimisation
Narendra D. Londhe; R.S. Anand
International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 82 - 98
The concept of Superharmonic Imaging (SHI) evolved because of non-linear propagation of ultrasound in biological. In this work, the comparison of fundamental, second and superharmonic components are presented, which is associated with amplitude and propagation distance along on-axis and off-axis as well. The parameters associated with imaging quality are: lateral and axial resolutions; depth of field and Signal to Noise Ratio (SNR). The trade-offs among above-mentioned four aspects of fundamental, second harmonic and superharmonic fields and relating them to system parameters such as aperture size, f-number, focal depth, central frequency and applied pressure help in superharmonic beam optimisation, which further enhances imaging ability.

]]> 10.1504/IJBET.2012.045359 International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 82 - 98 Narendra D. Londhe; R.S. Anand Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India. ' Department of Electrical Engineering, Indian Institute of Technology Roorkee, Roorkee, India harmonic imaging superharmonic beam optimisation KZK equation soft tissue ultrasound pulses biomedical technology. 2012-02-06T23:20:50-05:00 8 1 82 98 2012-02-06T23:20:50-05:00 http://www.inderscience.com/link.php?id=45360 The purpose of this study was to validate a Bioelectrical Impedance Analysis (BIA) equation for prediction of Bone Mineral Content (BMC) against Dual energy X-ray Absorptiometry (DXA) in Indian adults. Healthy 113 subjects were investigated by two methods: BMC was measured by DXA and bioelectrical impedance at various frequencies was measured by a commercial segmental multi-frequency BIA instrument. Body parameters were derived from impedance data and a new BIA equation was developed for the estimation of BMC, which exhibited high correlation and low prediction error. It was found valid in subjects with large variations in Body Mass (BM) and age. Estimation of bone mineral content from bioelectrical impedance analysis in Indian adults aged 23–81 years: a comparison with dual energy X-ray absorptiometry
B.R. Patil; D.P. Patkar; S.A. Mandlik; M.M. Kuswarkar; G.D. Jindal
International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 99 - 114
The purpose of this study was to validate a Bioelectrical Impedance Analysis (BIA) equation for prediction of Bone Mineral Content (BMC) against Dual energy X-ray Absorptiometry (DXA) in Indian adults. Healthy 113 subjects were investigated by two methods: BMC was measured by DXA and bioelectrical impedance at various frequencies was measured by a commercial segmental multi-frequency BIA instrument. Body parameters were derived from impedance data and a new BIA equation was developed for the estimation of BMC, which exhibited high correlation and low prediction error. It was found valid in subjects with large variations in Body Mass (BM) and age.

]]> 10.1504/IJBET.2012.045360 International Journal of Biomedical Engineering and Technology, Vol. 8, No. 1 (2012) pp. 99 - 114 B.R. Patil; D.P. Patkar; S.A. Mandlik; M.M. Kuswarkar; G.D. Jindal Department of Instrumentation Engineering, Bharati Vidyapeeth College of Engineering, Sector no.7, Kharghar, C. B. D., Navi Mumbai 400 614, India. ' MRI Centre, Dr. Balabhai Nanavati Hospital, Vile Parle (West), Mumbai 400 056, India. ' Bio-Medical Section, Electronics Division, Modular Laboratories, Bhabha Atomic Research Centre, Mumbai 400 085, India. ' Bio-Medical Section, Electronics Division, Modular Laboratories, Bhabha Atomic Research Centre, Mumbai 400 085, India. ' Bio-Medical Section, Electronics Division, Modular Laboratories, Bhabha Atomic Research Centre, Mumbai 400 085, India bioelectrical impedance analysis bone mineral content body parameters DXA dual energy X-ray absorptiometry India adults body mass age adult bones. 2012-02-06T23:20:50-05:00 8 1 99 114 2012-02-06T23:20:50-05:00