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For: Segato A, Marzullo A, Calimeri F, De Momi E. Artificial intelligence for brain diseases: A systematic review. APL Bioeng 2020;4:041503. [PMID: 33094213 DOI: 10.1063/5.0011697] [Cited by in Crossref: 32] [Cited by in F6Publishing: 33] [Article Influence: 10.7] [Reference Citation Analysis]
Number Citing Articles
1 Hou Y, Zhang L, Chen X, Wang Y, Jiang T, Qi Q, Zhang C, Shi C. Study on brain function of the frontal lobe in patients with functional gastroduodenal disease by near-infrared functional imaging. Biomedicine & Pharmacotherapy 2023;158:114182. [DOI: 10.1016/j.biopha.2022.114182] [Reference Citation Analysis]
2 Yacob YM, Alquran H, Mustafa WA, Alsalatie M, Sakim HAM, Lola MS. H. pylori Related Atrophic Gastritis Detection Using Enhanced Convolution Neural Network (CNN) Learner. Diagnostics 2023;13:336. [DOI: 10.3390/diagnostics13030336] [Reference Citation Analysis]
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8 Barile B, Ashtari P, Stamile C, Marzullo A, Maes F, Durand-dubief F, Van Huffel S, Sappey-marinier D. Classification of multiple sclerosis clinical profiles using machine learning and grey matter connectome. Front Robot AI 2022;9:926255. [DOI: 10.3389/frobt.2022.926255] [Reference Citation Analysis]
9 Karpychev V, Balatskaya A, Utyashev N, Pedyash N, Zuev A, Dragoy O, Fedele T. Epileptogenic high-frequency oscillations present larger amplitude both in mesial temporal and neocortical regions. Front Hum Neurosci 2022;16:984306. [DOI: 10.3389/fnhum.2022.984306] [Reference Citation Analysis]
10 Daripa B, Lucchese S. Artificial Intelligence-Aided Headache Classification Based on a Set of Questionnaires: A Short Review. Cureus 2022. [DOI: 10.7759/cureus.29514] [Reference Citation Analysis]
11 di Noia C, Grist JT, Riemer F, Lyasheva M, Fabozzi M, Castelli M, Lodi R, Tonon C, Rundo L, Zaccagna F. Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI. Diagnostics 2022;12:2125. [DOI: 10.3390/diagnostics12092125] [Reference Citation Analysis]
12 Rahman Z, Pasam T, Kr R, Dandekar MP. Binary Classification Model of Machine Learning Detected Altered Gut Integrity in Controlled-Cortical Impact Model of Traumatic Brain Injury. Int J Neurosci 2022;:1-14. [PMID: 35758006 DOI: 10.1080/00207454.2022.2095271] [Reference Citation Analysis]
13 Jaiswal AK, Jamal SB, Gabriel Rodrigues Gomes L, Profeta R, Sales-campos H, Oliveira CJF, Figueira Aburjaile F, Tiwari S, Barh D, Silva MVD, de Castro Soares S, Azevedo V. Neuroinformatics Insights towards Multiple Neurosyphilis Complications. Venereology 2022;1:135-160. [DOI: 10.3390/venereology1010010] [Reference Citation Analysis]
14 Silva RDCD, Jenkyn TR, Carranza VA. Enhanced Pre-Processing for Deep Learning in MRI Whole Brain Segmentation using Orthogonal Moments. Brain Multiphysics 2022. [DOI: 10.1016/j.brain.2022.100049] [Reference Citation Analysis]
15 Kaur G, Walvekar S, Thawkar B, Chintamaneni M. Recent Advances of Artificial Intelligence Tools in Attention-Deficit Hyperactivity Disorder (ADHD). CPSP 2022;11:18-29. [DOI: 10.2174/2211556011666220607112528] [Reference Citation Analysis]
16 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]
17 Sun J, Yuan X, M.a B. Application of Artificial Intelligence Nuclear Medicine Automated Images Based on Deep Learning in Tumor Diagnosis. Journal of Healthcare Engineering 2022;2022:1-10. [DOI: 10.1155/2022/7247549] [Reference Citation Analysis]
18 Mládek A, Gerla V, Skalický P, Vlasák A, Zazay A, Lhotská L, Beneš V Sr, Beneš V Jr, Bradáč O. Prediction of Shunt Responsiveness in Suspected Patients With Normal Pressure Hydrocephalus Using the Lumbar Infusion Test: A Machine Learning Approach. Neurosurgery 2022. [PMID: 35080523 DOI: 10.1227/NEU.0000000000001838] [Reference Citation Analysis]
19 Chandra J, Rangaswamy M, Banerjee B, Prajapati A, Akhtar Z, Sakauye K, Joseph A. Applications of artificial intelligence to neurological disorders: current technologies and open problems. Augmenting Neurological Disorder Prediction and Rehabilitation Using Artificial Intelligence 2022. [DOI: 10.1016/b978-0-323-90037-9.00005-9] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
20 Herzog NJ, Magoulas GD. Transfer Learning and Magnetic Resonance Imaging Techniques for the Deep Neural Network-Based Diagnosis of Early Cognitive Decline and Dementia. Computational Intelligence Methods for Bioinformatics and Biostatistics 2022. [DOI: 10.1007/978-3-031-20837-9_5] [Reference Citation Analysis]
21 Nalepa J. AIM and Brain Tumors. Artificial Intelligence in Medicine 2022. [DOI: 10.1007/978-3-030-64573-1_284] [Reference Citation Analysis]
22 Moccia S, De Momi E. AIM in Medical Robotics. Artificial Intelligence in Medicine 2022. [DOI: 10.1007/978-3-030-64573-1_64] [Reference Citation Analysis]
23 Mala S, Nagarajan B, Sangeetha G, Suganthi J. Oncology with Artificial Intelligence: Classification of Cancer Using Deep Learning Techniques. AI and IoT for Sustainable Development in Emerging Countries 2022. [DOI: 10.1007/978-3-030-90618-4_27] [Reference Citation Analysis]
24 Banerjee D, Rajput D, Banerjee S, Saharan VA. Artificial Intelligence and Its Applications in Drug Discovery, Formulation Development, and Healthcare. Computer Aided Pharmaceutics and Drug Delivery 2022. [DOI: 10.1007/978-981-16-5180-9_11] [Reference Citation Analysis]
25 Alagha MA, Young-gough A, Lyndon M, Walker X, Cobb J, Celi LA, Waters DL. AIM and Patient Safety. Artificial Intelligence in Medicine 2022. [DOI: 10.1007/978-3-030-64573-1_272] [Reference Citation Analysis]
26 Cauteruccio F. Alignment of Microarray Data. Methods in Molecular Biology 2022. [DOI: 10.1007/978-1-0716-1839-4_14] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
27 Herzog NJ, Magoulas GD. Machine Learning-Supported MRI Analysis of Brain Asymmetry for Early Diagnosis of Dementia. Studies in Computational Intelligence 2022. [DOI: 10.1007/978-3-030-91103-4_3] [Reference Citation Analysis]
28 Lim MJR. Letter: Machine Learning and Artificial Intelligence in Neurosurgery: Status, Prospects, and Challenges. Neurosurgery 2021;89:E333-4. [PMID: 34498686 DOI: 10.1093/neuros/nyab337] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
29 Helaly HA, Badawy M, Haikal AY. Deep Learning Approach for Early Detection of Alzheimer's Disease. Cognit Comput 2021;:1-17. [PMID: 34745371 DOI: 10.1007/s12559-021-09946-2] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
30 Loh HW, Hong W, Ooi CP, Chakraborty S, Barua PD, Deo RC, Soar J, Palmer EE, Acharya UR. Application of Deep Learning Models for Automated Identification of Parkinson's Disease: A Review (2011-2021). Sensors (Basel) 2021;21:7034. [PMID: 34770340 DOI: 10.3390/s21217034] [Cited by in Crossref: 8] [Cited by in F6Publishing: 9] [Article Influence: 4.0] [Reference Citation Analysis]
31 Dashwood M, Churchhouse G, Young M, Kuruvilla T. Artificial intelligence as an aid to diagnosing dementia: an overview. Prog Neurol Psychiatry 2021;25:42-7. [DOI: 10.1002/pnp.721] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
32 Zhang Z, Li G, Xu Y, Tang X. Application of Artificial Intelligence in the MRI Classification Task of Human Brain Neurological and Psychiatric Diseases: A Scoping Review. Diagnostics (Basel) 2021;11:1402. [PMID: 34441336 DOI: 10.3390/diagnostics11081402] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
33 Afrasiabi A, Keane JT, Heng JI, Palmer EE, Lovell NH, Alinejad-Rokny H. Quantitative neurogenetics: applications in understanding disease. Biochem Soc Trans 2021:BST20200732. [PMID: 34282824 DOI: 10.1042/BST20200732] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
34 Kim KH, Koo H, Lee B, Yoon S, Sohn M. Cerebral hemorrhage detection and localization with medical imaging for cerebrovascular disease diagnosis and treatment using explainable deep learning. J Korean Phys Soc 2021;79:321-7. [DOI: 10.1007/s40042-021-00202-2] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
35 Moccia S, De Momi E. AIM in Medical Robotics. Artificial Intelligence in Medicine 2021. [DOI: 10.1007/978-3-030-58080-3_64-1] [Reference Citation Analysis]
36 Mathew AA, S. V. A Review on Sleep Disorder Analysis and Applications Based on Artificial Intelligence. Advances in Medical Technologies and Clinical Practice 2021. [DOI: 10.4018/978-1-7998-8018-9.ch002] [Reference Citation Analysis]
37 Alagha MA, Young-gough A, Lyndon M, Walker X, Cobb J, Celi LA, Waters DL. AIM and Patient Safety. Artificial Intelligence in Medicine 2021. [DOI: 10.1007/978-3-030-58080-3_272-1] [Reference Citation Analysis]
38 Herzog NJ, Magoulas GD. Deep Learning of Brain Asymmetry Images and Transfer Learning for Early Diagnosis of Dementia. Proceedings of the International Neural Networks Society 2021. [DOI: 10.1007/978-3-030-80568-5_5] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
39 Nalepa J. AIM and Brain Tumors. Artificial Intelligence in Medicine 2021. [DOI: 10.1007/978-3-030-58080-3_284-1] [Reference Citation Analysis]