By Dr Imran Razzak

Journal articles

Hering A; Häger S; Moltz J; Lessmann N; Heldmann S; van Ginneken B, 2021, 'CNN-based lung CT registration with multiple anatomical constraints.', Med Image Anal, 72, pp. 102139, http://dx.doi.org/10.1016/j.media.2021.102139

Caballo M; Hernandez AM; Lyu SH; Teuwen J; Mann RM; van Ginneken B; Boone JM; Sechopoulos I, 2021, 'Computer-aided diagnosis of masses in breast computed tomography imaging: deep learning model with combined handcrafted and convolutional radiomic features.', J Med Imaging (Bellingham), 8, pp. 024501, http://dx.doi.org/10.1117/1.JMI.8.2.024501

Çallı E; Sogancioglu E; van Ginneken B; van Leeuwen KG; Murphy K, 2021, 'Deep learning for chest X-ray analysis: A survey.', Med Image Anal, 72, pp. 102125, http://dx.doi.org/10.1016/j.media.2021.102125

Jacobs C; Setio AAA; Scholten ET; Gerke PK; Bhattacharya H; M Hoesein FA; Brink M; Ranschaert E; de Jong PA; Silva M; Geurts B; Chung K; Schalekamp S; Meersschaert J; Devaraj A; Pinsky PF; Lam SC; van Ginneken B; Farahani K, 2021, 'Deep Learning for Lung Cancer Detection on Screening CT Scans: Results of a Large-Scale Public Competition and an Observer Study with 11 Radiologists.', Radiol Artif Intell, 3, pp. e210027, http://dx.doi.org/10.1148/ryai.2021210027

Venkadesh KV; Setio AAA; Schreuder A; Scholten ET; Chung K; W Wille MM; Saghir Z; van Ginneken B; Prokop M; Jacobs C, 2021, 'Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.', Radiology, 300, pp. 438 - 447, http://dx.doi.org/10.1148/radiol.2021204433

Çallı E; Murphy K; Kurstjens S; Samson T; Herpers R; Smits H; Rutten M; van Ginneken B, 2021, 'Deep learning with robustness to missing data: A novel approach to the detection of COVID-19.', PLoS One, 16, pp. e0255301, http://dx.doi.org/10.1371/journal.pone.0255301

Hendrix N; Scholten E; Vernhout B; Bruijnen S; Maresch B; de Jong M; Diepstraten S; Bollen S; Schalekamp S; de Rooij M; Scholtens A; Hendrix W; Samson T; Sharon Ong L-L; Postma E; van Ginneken B; Rutten M, 2021, 'Development and Validation of a Convolutional Neural Network for Automated Detection of Scaphoid Fractures on Conventional Radiographs.', Radiol Artif Intell, 3, pp. e200260, http://dx.doi.org/10.1148/ryai.2021200260

van Ginneken B, 2021, 'The Potential of Artificial Intelligence to Analyze Chest Radiographs for Signs of COVID-19 Pneumonia.', Radiology, 299, pp. E214 - E215, http://dx.doi.org/10.1148/radiol.2020204238

Naseem U; Razzak I; Musial K; Imran M, 2020, 'Transformer based Deep Intelligent Contextual Embedding for Twitter sentiment analysis', Future Generation Computer Systems, 113, pp. 58 - 69, http://dx.doi.org/10.1016/j.future.2020.06.050

Razzak I; Zafar K; Imran M; Xu G, 2020, 'Randomized nonlinear one-class support vector machines with bounded loss function to detect of outliers for large scale IoT data', Future Generation Computer Systems, 112, pp. 715 - 723, http://dx.doi.org/10.1016/j.future.2020.05.045

Naz S; Khan NH; Zahoor S; Razzak MI, 2020, 'Deep OCR for Arabic script-based language like Pastho', Expert Systems, 37, http://dx.doi.org/10.1111/exsy.12565

Saxena A; Pare S; Meena MS; Gupta D; Gupta A; Razzak I; Lin CT; Prasad M, 2020, 'A two-phase approach for semi-supervised feature selection', Algorithms, 13, http://dx.doi.org/10.3390/A13090215

Razzak MI; Imran M; Xu G, 2020, 'Big data analytics for preventive medicine', Neural Computing and Applications, 32, pp. 4417 - 4451, http://dx.doi.org/10.1007/s00521-019-04095-y

Zahoor S; Naz S; Khan NH; Razzak MI, 2020, 'Deep optical character recognition: A case of Pashto language', Journal of Electronic Imaging, 29, http://dx.doi.org/10.1117/1.JEI.29.2.023002

Rehman A; Naz S; Razzak MI; Akram F; Imran M, 2020, 'A Deep Learning-Based Framework for Automatic Brain Tumors Classification Using Transfer Learning', Circuits, Systems, and Signal Processing, 39, pp. 757 - 775, http://dx.doi.org/10.1007/s00034-019-01246-3

Naseer A; Rani M; Naz S; Razzak MI; Imran M; Xu G, 2020, 'Refining Parkinson’s neurological disorder identification through deep transfer learning', Neural Computing and Applications, 32, pp. 839 - 854, http://dx.doi.org/10.1007/s00521-019-04069-0

Razzak I; Saris RA; Blumenstein M; Xu G, 2020, 'Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection', Neural Networks, 121, pp. 441 - 451, http://dx.doi.org/10.1016/j.neunet.2019.08.030

Humpire-Mamani GE; Bukala J; Scholten ET; Prokop M; van Ginneken B; Jacobs C, 2020, 'Fully Automatic Volume Measurement of the Spleen at CT Using Deep Learning.', Radiol Artif Intell, 2, pp. e190102, http://dx.doi.org/10.1148/ryai.2020190102

Schreuder A; Jacobs C; Scholten ET; van Ginneken B; Schaefer-Prokop CM; Prokop M, 2020, 'Typical CT Features of Intrapulmonary Lymph Nodes: A Review.', Radiol Cardiothorac Imaging, 2, pp. e190159, http://dx.doi.org/10.1148/ryct.2020190159

Saeed Z; Abbasi RA; Razzak I; Maqbool O; Sadaf A; Xu G, 2019, 'Enhanced Heartbeat Graph for emerging event detection on Twitter using time series networks', Expert Systems with Applications, 136, pp. 115 - 132, http://dx.doi.org/10.1016/j.eswa.2019.06.005

Razzak MI; Imran M; Xu G, 2019, 'Efficient Brain Tumor Segmentation with Multiscale Two-Pathway-Group Conventional Neural Networks', IEEE Journal of Biomedical and Health Informatics, 23, pp. 1911 - 1919, http://dx.doi.org/10.1109/JBHI.2018.2874033

Asghar MZ; Razzak MI; Virk SM, 2019, 'A Special Section on Social Computing in Health Informatics', JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 9, pp. 1167 - 1170, http://dx.doi.org/10.1166/jmihi.2019.2697

Saeed Z; Ayaz Abbasi R; Razzak MI; Xu G, 2019, 'Event Detection in Twitter Stream Using Weighted Dynamic Heartbeat Graph Approach [Application Notes]', IEEE Computational Intelligence Magazine, 14, pp. 29 - 38, http://dx.doi.org/10.1109/MCI.2019.2919395

Saeed Z; Abbasi RA; Maqbool O; Sadaf A; Razzak I; Daud A; Aljohani NR; Xu G, 2019, 'What’s Happening Around the World? A Survey and Framework on Event Detection Techniques on Twitter', Journal of Grid Computing, 17, pp. 279 - 312, http://dx.doi.org/10.1007/s10723-019-09482-2

Razzak I; Blumenstein M; Xu G, 2019, 'Multiclass Support Matrix Machines by Maximizing the Inter-Class Margin for Single Trial EEG Classification', IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27, pp. 1117 - 1127, http://dx.doi.org/10.1109/TNSRE.2019.2913142

Ahmed SB; Naz S; Swati S; Razzak MI, 2019, 'Handwritten Urdu character recognition using one-dimensional BLSTM classifier', Neural Computing and Applications, 31, pp. 1143 - 1151, http://dx.doi.org/10.1007/s00521-017-3146-x

Rehman A; Naz S; Razzak MI, 2019, 'Writer identification using machine learning approaches: a comprehensive review', Multimedia Tools and Applications, 78, pp. 10889 - 10931, http://dx.doi.org/10.1007/s11042-018-6577-1

Ahmed SB; Naz S; Razzak MI; Yusof R, 2019, 'Arabic cursive text recognition from natural scene images', Applied Sciences (Switzerland), 9, http://dx.doi.org/10.3390/app9020236

Ahmed SB; Naz S; Razzak MI; Yusof RB, 2019, 'A Novel Dataset for English-Arabic Scene Text Recognition (EASTR)-42K and Its Evaluation Using Invariant Feature Extraction on Detected Extremal Regions', IEEE Access, 7, pp. 19801 - 19820, http://dx.doi.org/10.1109/ACCESS.2019.2895876

Rehman A; Naz S; Razzak MI; Hameed IA, 2019, 'Automatic Visual Features for Writer Identification: A Deep Learning Approach', IEEE Access, 7, pp. 17149 - 17157, http://dx.doi.org/10.1109/ACCESS.2018.2890810

Ahmed SB; Hameed IA; Naz S; Razzak MI; Yusof R, 2019, 'Evaluation of handwritten Urdu text by integration of MNIST dataset learning experience', IEEE Access, 7, pp. 153566 - 153578, http://dx.doi.org/10.1109/ACCESS.2019.2946313

Razzak I; Hameed IA; Xu G, 2019, 'Robust Sparse Representation and Multiclass Support Matrix Machines for the Classification of Motor Imagery EEG Signals', IEEE Journal of Translational Engineering in Health and Medicine, 7, http://dx.doi.org/10.1109/JTEHM.2019.2942017

Naz S; Umar AI; Ahmed SB; Ahmad R; Shirazi SH; Razzak MI; Zaman A, 2018, 'Statistical features extraction for character recognition using recurrent neural network', Pakistan Journal of Statistics, 34, pp. 47 - 53

Naz S; Umar AI; Ahmad R; Siddiqi I; Ahmed SB; Razzak MI; Shafait F, 2017, 'Urdu Nastaliq recognition using convolutional–recursive deep learning', Neurocomputing, 243, pp. 80 - 87, http://dx.doi.org/10.1016/j.neucom.2017.02.081

Shirazi SH; Umar AI; Haq N; Naz S; Razzak MI; Zaib A, 2017, 'Extreme learning machine based microscopic red blood cells classification', Cluster Computing, 21, pp. 691 - 701, http://dx.doi.org/10.1007/s10586-017-0978-1

Bin Ahmed S; Naz S; Swati S; Razzak I; Umar AI; Ali Khan A, 2017, 'UCOM offline dataset-an Urdu handwritten dataset generation', International Arab Journal of Information Technology, 14, pp. 239 - 245

Naz S; Umar AI; Ahmad R; Ahmed SB; Shirazi SH; Razzak MI, 2017, 'Urdu Nasta’liq text recognition system based on multi-dimensional recurrent neural network and statistical features', Neural Computing and Applications, 28, pp. 219 - 231, http://dx.doi.org/10.1007/s00521-015-2051-4

Naz S; Umar AI; Ahmed R; Razzak MI; Rashid SF; Shafait F, 2016, 'Urdu Nasta’liq text recognition using implicit segmentation based on multi-dimensional long short term memory neural networks', SpringerPlus, 5, http://dx.doi.org/10.1186/s40064-016-3442-4

Ghamdi HA; Alshammari R; Razzak MI, 2016, 'An ontology-based system to predict hospital readmission within 30 days', International Journal of Healthcare Management, 9, pp. 236 - 244, http://dx.doi.org/10.1080/20479700.2016.1139768

Al Moamary E; Alshammari R; Razzak MI, 2016, 'Blood bank control system: An ontology', Advanced Science Letters, 22, pp. 2822 - 2826, http://dx.doi.org/10.1166/asl.2016.7086

Al Asaimi AA; Razzak MI; Alshammari R, 2016, 'Developing ontology for RFID based infant protection system', Advanced Science Letters, 22, pp. 2759 - 2763, http://dx.doi.org/10.1166/asl.2016.7085

Naz S; Umar AI; Shirazi SH; Ahmed SB; Razzak MI; Siddiqi I, 2016, 'Segmentation techniques for recognition of Arabic-like scripts: A comprehensive survey', Education and Information Technologies, 21, pp. 1225 - 1241, http://dx.doi.org/10.1007/s10639-015-9377-5

Alsomali W; Razzak I; Alshammari R, 2016, 'Development of ontology for penicillin-Related adverse events', Journal of Medical Imaging and Health Informatics, 6, pp. 620 - 626, http://dx.doi.org/10.1166/jmihi.2016.1724

Ahmed SB; Naz S; Razzak MI; Rashid SF; Afzal MZ; Breuel TM, 2016, 'Evaluation of cursive and non-cursive scripts using recurrent neural networks', Neural Computing and Applications, 27, pp. 603 - 613, http://dx.doi.org/10.1007/s00521-015-1881-4

Naz S; Umar AI; Ahmad R; Ahmed SB; Shirazi SH; Siddiqi I; Razzak MI, 2016, 'Offline cursive Urdu-Nastaliq script recognition using multidimensional recurrent neural networks', Neurocomputing, 177, pp. 228 - 241, http://dx.doi.org/10.1016/j.neucom.2015.11.030

Shirazi SH; Umar AI; Naz S; Razzak MI, 2016, 'Efficient leukocyte segmentation and recognition in peripheral blood image', Technology and Health Care, 24, pp. 335 - 347, http://dx.doi.org/10.3233/THC-161133

Razzak MI; Alhaqbani B, 2015, 'Multilevel fusion for fast online signature recognition using multi-section VQ and time modelling', Neural Computing and Applications, 26, pp. 1117 - 1127, http://dx.doi.org/10.1007/s00521-014-1779-6

Mahmood L; Shirazi SF; Naz S; Shirazi SH; Razzak MI; Umar AI; Ashraf SS, 2015, 'Adaptive filtering algorithms for channel equalization in wireless communication', Indian Journal of Science and Technology, 8, http://dx.doi.org/10.17485/ijst/2015/v8i17/57805

Razzak MI; Alhaqbani B, 2015, 'Automatic detection of malarial parasite using microscopic blood images', Journal of Medical Imaging and Health Informatics, 5, pp. 591 - 598, http://dx.doi.org/10.1166/jmihi.2015.1417

Daghistani T; Shammari RA; Razzak MI, 2015, 'Discovering diabetes complications: An ontology based model', Acta Informatica Medica, 23, pp. 385 - 392, http://dx.doi.org/10.5455/aim.2015.23.385-392

Back to profile page