1 |
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] [Reference Citation Analysis]
|
2 |
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]
|
3 |
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: 1.0] [Reference Citation Analysis]
|
4 |
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] [Reference Citation Analysis]
|
5 |
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: 1] [Article Influence: 1.0] [Reference Citation Analysis]
|
6 |
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: 3] [Article Influence: 3.0] [Reference Citation Analysis]
|
7 |
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]
|
8 |
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]
|
9 |
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] [Reference Citation Analysis]
|
10 |
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]
|
11 |
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: 1] [Article Influence: 1.0] [Reference Citation Analysis]
|
12 |
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] [Reference Citation Analysis]
|