Computer Methods and Programs in Biomedicine, Volume 173

Volume 173, May 2019

Section I: Methodology

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  Alan R. Andrade, Luis H. S. Vogado, Rodrigo de Melo Souza Veras, Romuere R. V. e Silva, Flávio H. D. Araújo, Fátima N. S. de Medeiros:
  Recent computational methods for white blood cell nuclei segmentation: A comparative study. 1-14
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  Parisa Yazdjerdi, Nader Meskin, Mohammad Al-Naemi, Ala-Eddin Al Moustafa, Levente Kovács:
  Reinforcement learning-based control of tumor growth under anti-angiogenic therapy. 15-26
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  Mirela T. Cazzolato, Lucas C. Scabora, Marcos R. Nesso Jr., Luis Fernando Milano Oliveira, Alceu Ferraz Costa, Daniel S. Kaster, Marcel Koenigkam-Santos, Paulo Mazzoncini de Azevedo Marques, Caetano Traina Jr., Agma J. M. Traina:
  dp-BREATH: Heat maps and probabilistic classification assisting the analysis of abnormal lung regions. 27-34
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  Katrin Sippel, Julia Moser, Franziska Schleger, Hubert Preissl, Wolfgang Rosenstiel, Martin Spüler:
  Fully Automated R-peak Detection Algorithm (FLORA) for fetal magnetoencephalographic data. 35-41

Section II: Systems and Programs

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  Cristian D. Ríos-Urrego, Juan Camilo Vásquez-Correa, Jesús Francisco Vargas-Bonilla, Elmar Nöth, Francisco Lopera, Juan Rafael Orozco-Arroyave:
  Analysis and evaluation of handwriting in patients with Parkinson's disease using kinematic, geometrical, and non-linear features. 43-52

Section III: Experiences with Methods, Systems and Programs

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  R. K. Tripathy, Mario Roberto Arrieta Paternina, Juan G. Arrieta, Alejandro Zamora-Méndez, Ganesh R. Naik:
  Automated detection of congestive heart failure from electrocardiogram signal using Stockwell transform and hybrid classification scheme. 53-65

Section II: Systems and Programs

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  Miguel Marco, Eugenio Giner, José Ramón Caeiro-Rey, Maria Henar Miguelez, Ricardo Larraínzar-Garijo:
  Numerical modelling of hip fracture patterns in human femur. 67-75

Section III: Experiences with Methods, Systems and Programs

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  Henning Höfener, André Homeyer, Mareike Förster, Norbert Drieschner, Hans-Ulrich Schildhaus, Horst K. Hahn:
  Automated density-based counting of FISH amplification signals for HER2 status assessment. 77-85
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  Dildar Hussain, Seung-Moo Han:
  Computer-aided osteoporosis detection from DXA imaging. 87-107

Section II: Systems and Programs

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  Chieh-Chen Wu, Wen-Ding Hsu, Md. Mohaimenul Islam, Tahmina Nasrin Poly, Hsuan-Chia Yang, Phung-Anh (Alex) Nguyen, Yao-Chin Wang, Yu-Chuan (Jack) Li:
  An artificial intelligence approach to early predict non-ST-elevation myocardial infarction patients with chest pain. 109-117

Section III: Experiences with Methods, Systems and Programs

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  Quoc Dang Vu, Jin Tae Kwak:
  A dense multi-path decoder for tissue segmentation in histopathology images. 119-129

Section II: Systems and Programs

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  Tugce Kantar Ugur, Aykut Erdamar:
  An efficient automatic arousals detection algorithm in single channel EEG. 131-138

Section I: Methodology

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  Adam G. Polak, Dariusz Wysoczanski, Janusz Mroczka:
  Effects of homogeneous and heterogeneous changes in the lung periphery on spirometry results. 139-145

Section II: Systems and Programs

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  Rohini Palanisamy, S. Sundar, S. Ramakrishnan:
  Characterization of Alzheimer conditions in MR images using volumetric and sagittal brainstem texture features. 147-155

Section III: Experiences with Methods, Systems and Programs

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  Sachin Taran, Varun Bajaj:
  Emotion recognition from single-channel EEG signals using a two-stage correlation and instantaneous frequency-based filtering method. 157-165

Section II: Systems and Programs

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  Jun Park, Giorgos Bakoyannis, Constantin T. Yiannoutsos:
  Semiparametric competing risks regression under interval censoring using the R package intccr. 167-176

Section I: Methodology

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  Mieke Deschepper, Kristof Eeckloo, Dirk Vogelaers, Willem Waegeman:
  A hospital wide predictive model for unplanned readmission using hierarchical ICD data. 177-183
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  Bo Sun, Yinghui Zhang, Jun He, Yongkang Xiao, Rong Xiao:
  An automatic diagnostic network using skew-robust adversarial discriminative domain adaptation to evaluate the severity of depression. 185-195