Computer Methods and Programs in Biomedicine, Volume 178

Volume 178, September 2019

Section IV: Classification and interpretation

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  Ben van Noorden, Jennifer L. Knopp, J. Geoffrey Chase:
  A subcutaneous insulin pharmacokinetic model for insulin Detemir. 1-9
• 
  Ardo van den Hout, Mei Sum Chan, Fiona E. Matthews:
  Estimation of life expectancies using continuous-time multi-state models. 11-18

Section II: Biomedical signal and image processing methods

• 
  Dihong Jiang, Yu Ma, Yuanyuan Wang:
  Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds. 19-30
• 
  Damian J. Matuszewski, Ida-Maria Sintorn:
  Reducing the U-Net size for practical scenarios: Virus recognition in electron microscopy images. 31-39

Section V: Others

• 
  Bor-Shing Lin, Yao-Kuang Huang, Bor-Shyh Lin:
  Design of smart EEG cap. 41-46

Section IV: Classification and interpretation

• 
  Samaneh Layeghian Javan, Mohammad Mehdi Sepehri, Malihe Layeghian Javan, Toktam Khatibi:
  An intelligent warning model for early prediction of cardiac arrest in sepsis patients. 47-58
• 
  Resat Özgür Doruk, Ahmed H. Mohsin:
  Automatic control of Hypothalamus-Pituitary-Adrenal axis dynamics. 59-75
• 
  Wen Shi, Peter Xiaoping Liu, Minhua Zheng:
  A new volumetric geometric model for cutting procedures in surgical simulation. 77-84

Section III: Modelling & Simulation

• 
  Laura Oliveira Moraes, Carlos Eduardo Pedreira, Susana Barrena, Antonio López, Alberto Orfao:
  A decision-tree approach for the differential diagnosis of chronic lymphoid leukemias and peripheral B-cell lymphomas. 85-90

Section II: Biomedical signal and image processing methods

• 
  László Varga, Attila Kovács, Tamás Grósz, Géza Thury, Flóra Hadarits, Rózsa Dégi, József Dombi:
  Automatic segmentation of hyperreflective foci in OCT images. 91-103

Section V: Others

• 
  Beaulah Mary Robert, G. R. Brindha, Santhi Balachandran, G. Kanimozhi, Nagarajan Rajendra Prasad:
  Computational models for predicting anticancer drug efficacy: A multi linear regression analysis based on molecular, cellular and clinical data of oral squamous cell carcinoma cohort. 105-112

Section II: Biomedical signal and image processing methods

• 
  Edward J. Ciaccio, Elaine Y. Wan, Deepak S. Saluja, U. Rajendra Acharya, Nicholas S. Peters, Hasan Garan:
  Addressing challenges of quantitative methodologies and event interpretation in the study of atrial fibrillation. 113-122
• 
  Giorgos A. Giannakakis, Manolis Tsiknakis, Pelagia Vorgia:
  Focal epileptic seizures anticipation based on patterns of heart rate variability parameters. 123-133
• 
  Genlang Chen, Zhiqing Hong, Yongjuan Guo, Chaoyi Pang:
  A cascaded classifier for multi-lead ECG based on feature fusion. 135-143

Section V: Others

• 
  Elham Khorasani Buxton, Sameer Vohra, Yanhui Guo, Amanda Fogleman, Rushabh Patel:
  Pediatric population health analysis of southern and central Illinois region: A cross sectional retrospective study using association rule mining and multiple logistic regression. 145-153

Section II: Biomedical signal and image processing methods

• 
  Manabu Takamatsu, Noriko Yamamoto, Hiroshi Kawachi, Akiko Chino, Shoichi Saito, Masashi Ueno, Yuichi Ishikawa, Yutaka Takazawa, Kengo Takeuchi:
  Prediction of early colorectal cancer metastasis by machine learning using digital slide images. 155-161
• 
  Hai Chen, Xiaochen Yuan, Jianqing Li, Zhiyuan Pei, Xiaobin Zheng:
  Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection. 163-173

Section IV: Classification and interpretation

• 
  Silvia Oviedo, Iván Contreras, Arthur Bertachi, Carmen Quirós, Marga Giménez, Ignacio Conget, Josep Vehí:
  Minimizing postprandial hypoglycemia in Type 1 diabetes patients using multiple insulin injections and capillary blood glucose self-monitoring with machine learning techniques. 175-180
• 
  Oscar J. Perdomo, Hernán Rios, Francisco J. Rodríguez, Juan Sebastian Otálora Montenegro, Fabrice Mériaudeau, Henning Müller, Fabio A. González:
  Classification of diabetes-related retinal diseases using a deep learning approach in optical coherence tomography. 181-189
• 
  S. E. Samioti, Lefteris Benos, Ioannis E. Sarris:
  Effect of fractal-shaped outer boundary of glioblastoma multiforme on drug delivery. 191-199

Section II: Biomedical signal and image processing methods

• 
  Saptarshi Chatterjee, Debangshu Dey, Sugata Munshi:
  Integration of morphological preprocessing and fractal based feature extraction with recursive feature elimination for skin lesion types classification. 201-218

Section III: Modelling & Simulation

• 
  Aman Sharma, Rinkle Rani:
  C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods. 219-235

Section II: Biomedical signal and image processing methods

• 
  Kyoung Jin Noh, Sang Jun Park, Soochahn Lee:
  Scale-space approximated convolutional neural networks for retinal vessel segmentation. 237-246

Section V: Others

• 
  Vanja Lukovic, Sasa Cukovic, Danijela Milosevic, Goran Devedzic:
  An ontology-based module of the information system ScolioMedIS for 3D digital diagnosis of adolescent scoliosis. 247-263

Section IV: Classification and interpretation

• 
  Kao-Shang Shih, Chi-Pin Hsu, Che-Wei Liu, Lu-Lin Wang, Sheng-Mou Hou, Shang-Chih Lin:
  Comparison between different screening strategies to determine the statistical shape model of the pelvises for implant design. 265-273

Section II: Biomedical signal and image processing methods

• 
  Shao Xiang, Qiaokang Liang, Yucheng Hu, Peng Tang, Gianmarc Coppola, Dan Zhang, Wei Sun:
  AMC-Net: Asymmetric and multi-scale convolutional neural network for multi-label HPA classification. 275-287
• 
  Peng Tang, Qiaokang Liang, Xintong Yan, Shao Xiang, Wei Sun, Dan Zhang, Gianmarc Coppola:
  Efficient skin lesion segmentation using separable-Unet with stochastic weight averaging. 289-301

Section III: Modelling & Simulation

• 
  Ángel E. Esteban, Miguel López-Pérez, Adrián Colomer, María Á. Sales, Rafael Molina, Valery Naranjo:
  A new optical density granulometry-based descriptor for the classification of prostate histological images using shallow and deep Gaussian processes. 303-317

Section II: Biomedical signal and image processing methods

• 
  Haribalan Kumar, Steve V. DeSouza, Maxim S. Petrov:
  Automated pancreas segmentation from computed tomography and magnetic resonance images: A systematic review. 319-328

Section IV: Classification and interpretation

• 
  S. M. Lavezzi, Maurizio Rocchetti, P. Bettica, Stefania Petrini, Giuseppe De Nicolao:
  Assessing drug effect from distributional data: A population approach with application to Duchenne Muscular Dystrophy treatment. 329-342