By Dr Imran Razzak

Journal articles

Islam MR; Liu S; Biddle R; Razzak I; Wang X; Tilocca P; Xu G, 2021, 'Discovering dynamic adverse behavior of policyholders in the life insurance industry', Technological Forecasting and Social Change, 163, http://dx.doi.org/10.1016/j.techfore.2020.120486

Qayyum A; Razzak I; Tanveer M; Kumar A, 2021, 'Depth-wise dense neural network for automatic COVID19 infection detection and diagnosis', Annals of Operations Research, http://dx.doi.org/10.1007/s10479-021-04154-5

Khan MZ; Khan MUG; Saba T; Razzak I; Rehman A; Bahaj SA, 2021, 'Hot-Spot Zone Detection to Tackle Covid19 Spread by Fusing the Traditional Machine Learning and Deep Learning Approaches of Computer Vision', IEEE Access, 9, pp. 100040 - 100049, http://dx.doi.org/10.1109/ACCESS.2021.3094720

Yousaf W; Umar A; Shirazi SH; Khan Z; Razzak I; Zaka M, 2021, 'Patch-CNN: Deep learning for logo detection and brand recognition', Journal of Intelligent and Fuzzy Systems, 40, pp. 3849 - 3862, http://dx.doi.org/10.3233/JIFS-190660

Zhou SK; Greenspan H; Davatzikos C; Duncan JS; van Ginneken B; Madabhushi A; Prince JL; Rueckert D; Summers RM, 2021, 'A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises.', Proc IEEE Inst Electr Electron Eng, 109, pp. 820 - 838, http://dx.doi.org/10.1109/JPROC.2021.3054390

Bortsova G; González-Gonzalo C; Wetstein SC; Dubost F; Katramados I; Hogeweg L; Liefers B; van Ginneken B; Pluim JPW; Veta M; Sánchez CI; de Bruijne M, 2021, 'Adversarial attack vulnerability of medical image analysis systems: Unexplored factors.', Med Image Anal, 73, pp. 102141, http://dx.doi.org/10.1016/j.media.2021.102141

Meyer A; Chlebus G; Rak M; Schindele D; Schostak M; van Ginneken B; Schenk A; Meine H; Hahn HK; Schreiber A; Hansen C, 2021, 'Anisotropic 3D Multi-Stream CNN for Accurate Prostate Segmentation from Multi-Planar MRI.', Comput Methods Programs Biomed, 200, pp. 105821, http://dx.doi.org/10.1016/j.cmpb.2020.105821

Schreuder A; Scholten ET; van Ginneken B; Jacobs C, 2021, 'Artificial intelligence for detection and characterization of pulmonary nodules in lung cancer CT screening: ready for practice?', Transl Lung Cancer Res, 10, pp. 2378 - 2388, http://dx.doi.org/10.21037/tlcr-2020-lcs-06

van Leeuwen KG; Schalekamp S; Rutten MJCM; van Ginneken B; de Rooij M, 2021, 'Artificial intelligence in radiology: 100 commercially available products and their scientific evidence.', Eur Radiol, 31, pp. 3797 - 3804, http://dx.doi.org/10.1007/s00330-021-07892-z

Jacobs C; Schreuder A; van Riel SJ; Scholten ET; Wittenberg R; Wille MMW; de Hoop B; Sprengers R; Mets OM; Geurts B; Prokop M; Schaefer-Prokop C; van Ginneken B, 2021, 'Assisted versus Manual Interpretation of Low-Dose CT Scans for Lung Cancer Screening: Impact on Lung-RADS Agreement.', Radiol Imaging Cancer, 3, pp. e200160, http://dx.doi.org/10.1148/rycan.2021200160

Lessmann N; Sánchez CI; Beenen L; Boulogne LH; Brink M; Calli E; Charbonnier J-P; Dofferhoff T; van Everdingen WM; Gerke PK; Geurts B; Gietema HA; Groeneveld M; van Harten L; Hendrix N; Hendrix W; Huisman HJ; Išgum I; Jacobs C; Kluge R; Kok M; Krdzalic J; Lassen-Schmidt B; van Leeuwen K; Meakin J; Overkamp M; van Rees Vellinga T; van Rikxoort EM; Samperna R; Schaefer-Prokop C; Schalekamp S; Scholten ET; Sital C; Stöger JL; Teuwen J; Venkadesh KV; de Vente C; Vermaat M; Xie W; de Wilde B; Prokop M; van Ginneken B, 2021, 'Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence.', Radiology, 298, pp. E18 - E28, http://dx.doi.org/10.1148/radiol.2020202439

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

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