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For: Das S, Nayak G, Saba L, Kalra M, Suri JS, Saxena S. An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review. Computers in Biology and Medicine 2022. [DOI: 10.1016/j.compbiomed.2022.105273] [Cited by in Crossref: 8] [Cited by in F6Publishing: 7] [Article Influence: 8.0] [Reference Citation Analysis]
Number Citing Articles
1 Saxena S, Jena B, Mohapatra B, Gupta N, Kalra M, Scartozzi M, Saba L, Suri JS. Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigation. Comput Biol Med 2023;153:106492. [PMID: 36621191 DOI: 10.1016/j.compbiomed.2022.106492] [Reference Citation Analysis]
2 Zhang Q, Liang Y, Zhang Y, Tao Z, Li R, Bi H. A comparative study of attention mechanism based deep learning methods for bladder tumor segmentation. Int J Med Inform 2023;171:104984. [PMID: 36634475 DOI: 10.1016/j.ijmedinf.2023.104984] [Reference Citation Analysis]
3 Zhou T, Ruan S, Hu H. A literature survey of MR-based brain tumor segmentation with missing modalities. Comput Med Imaging Graph 2022;104:102167. [PMID: 36584536 DOI: 10.1016/j.compmedimag.2022.102167] [Reference Citation Analysis]
4 Samee NA, Ahmad T, Mahmoud NF, Atteia G, Abdallah HA, Rizwan A. Clinical Decision Support Framework for Segmentation and Classification of Brain Tumor MRIs Using a U-Net and DCNN Cascaded Learning Algorithm. Healthcare (Basel) 2022;10. [PMID: 36553864 DOI: 10.3390/healthcare10122340] [Reference Citation Analysis]
5 Khanna NN, Maindarkar MA, Viswanathan V, Puvvula A, Paul S, Bhagawati M, Ahluwalia P, Ruzsa Z, Sharma A, Kolluri R, Krishnan PR, Singh IM, Laird JR, Fatemi M, Alizad A, Dhanjil SK, Saba L, Balestrieri A, Faa G, Paraskevas KI, Misra DP, Agarwal V, Sharma A, Teji JS, Al-Maini M, Nicolaides A, Rathore V, Naidu S, Liblik K, Johri AM, Turk M, Sobel DW, Miner M, Viskovic K, Tsoulfas G, Protogerou AD, Mavrogeni S, Kitas GD, Fouda MM, Kalra MK, Suri JS. Cardiovascular/Stroke Risk Stratification in Diabetic Foot Infection Patients Using Deep Learning-Based Artificial Intelligence: An Investigative Study. J Clin Med 2022;11. [PMID: 36431321 DOI: 10.3390/jcm11226844] [Reference Citation Analysis]
6 Chen C, Zhang T, Teng Y, Yu Y, Shu X, Zhang L, Zhao F, Xu J. Automated segmentation of craniopharyngioma on MR images using U-Net-based deep convolutional neural network. Eur Radiol 2022. [DOI: 10.1007/s00330-022-09216-1] [Reference Citation Analysis]
7 Lee P, Kim H, Zitouni MS, Khandoker A, Jelinek HF, Hadjileontiadis L, Lee U, Jeong Y. Trends in Smart Helmets With Multimodal Sensing for Health and Safety: Scoping Review. JMIR Mhealth Uhealth 2022;10:e40797. [PMID: 36378505 DOI: 10.2196/40797] [Reference Citation Analysis]
8 Jain PK, Sharma N, Kalra MK, Johri A, Saba L, Suri JS. Far wall plaque segmentation and area measurement in common and internal carotid artery ultrasound using U-series architectures: An unseen Artificial Intelligence paradigm for stroke risk assessment. Computers in Biology and Medicine 2022;149:106017. [DOI: 10.1016/j.compbiomed.2022.106017] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
9 Jain PK, Dubey A, Saba L, Khanna NN, Laird JR, Nicolaides A, Fouda MM, Suri JS, Sharma N. Attention-Based UNet Deep Learning Model for Plaque Segmentation in Carotid Ultrasound for Stroke Risk Stratification: An Artificial Intelligence Paradigm. JCDD 2022;9:326. [DOI: 10.3390/jcdd9100326] [Reference Citation Analysis]
10 Skandha SS, Agarwal M, Utkarsh K, Gupta SK, Koppula VK, Suri JS. A novel genetic algorithm-based approach for compression and acceleration of deep learning convolution neural network: an application in computer tomography lung cancer data. Neural Comput & Applic. [DOI: 10.1007/s00521-022-07567-w] [Reference Citation Analysis]
11 Suri JS, Maindarkar MA, Paul S, Ahluwalia P, Bhagawati M, Saba L, Faa G, Saxena S, Singh IM, Chadha PS, Turk M, Johri A, Khanna NN, Viskovic K, Mavrogeni S, Laird JR, Miner M, Sobel DW, Balestrieri A, Sfikakis PP, Tsoulfas G, Protogerou AD, Misra DP, Agarwal V, Kitas GD, Kolluri R, Teji JS, Al-maini M, Dhanjil SK, Sockalingam M, Saxena A, Sharma A, Rathore V, Fatemi M, Alizad A, Krishnan PR, Omerzu T, Naidu S, Nicolaides A, Paraskevas KI, Kalra M, Ruzsa Z, Fouda MM. Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID-19: A Narrative Review. Diagnostics 2022;12:1543. [DOI: 10.3390/diagnostics12071543] [Reference Citation Analysis]
12 Nillmani, Jain PK, Sharma N, Kalra MK, Viskovic K, Saba L, Suri JS. Four Types of Multiclass Frameworks for Pneumonia Classification and Its Validation in X-ray Scans Using Seven Types of Deep Learning Artificial Intelligence Models. Diagnostics (Basel) 2022;12:652. [PMID: 35328205 DOI: 10.3390/diagnostics12030652] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]