| Machine learning applications for differentiation of glioma from brain metastasis—a systematic review L Jekel, WR Brim, M von Reppert, L Staib, G Cassinelli Petersen, ... Cancers 14 (6), 1369, 2022 | 16 | 2022 |
| Machine learning in differentiating gliomas from primary CNS lymphomas: a systematic review, reporting quality, and risk of bias assessment GIC Petersen, J Shatalov, T Verma, WR Brim, H Subramanian, A Brackett, ... American Journal of Neuroradiology 43 (4), 526-533, 2022 | 11 | 2022 |
| Machine learning models for classifying high-and low-grade gliomas: a systematic review and quality of reporting analysis RC Bahar, S Merkaj, GI Cassinelli Petersen, N Tillmanns, H Subramanian, ... Frontiers in Oncology 12, 856231, 2022 | 7 | 2022 |
| Trends in development of novel machine learning methods for the identification of gliomas in datasets that include non-glioma images: a systematic review H Subramanian, R Dey, WR Brim, N Tillmanns, G Cassinelli Petersen, ... Frontiers in oncology 11, 788819, 2021 | 7 | 2021 |
| Identifying clinically applicable machine learning algorithms for glioma segmentation: recent advances and discoveries N Tillmanns, AE Lum, G Cassinelli, S Merkaj, T Verma, T Zeevi, L Staib, ... Neuro-Oncology Advances 4 (1), vdac093, 2022 | 5 | 2022 |
| Nimg-23. machine learning methods in glioma grade prediction: A systematic review R Bahar, S Merkaj, WR Brim, H Subramanian, T Zeevi, E Kazarian, M Lin, ... Neuro-Oncology 23 (Suppl 6), vi133, 2021 | 2 | 2021 |
| OTHR-15. Assessment of TRIPOD adherence in articles developing machine learning models for differentiation of glioma from brain metastasis L Jekel, WR Brim, GC Petersen, H Subramanian, T Zeevi, S Payabvash, ... Neuro-oncology Advances 3 (Suppl 3), iii17, 2021 | 2 | 2021 |
| Systematic Literature Review of Machine Learning Algorithms Using Pretherapy Radiologic Imaging for Glioma Molecular Subtype Prediction J Lost, T Verma, L Jekel, M von Reppert, N Tillmanns, S Merkaj, ... American Journal of Neuroradiology 44 (10), 1126-1134, 2023 | 1 | 2023 |
| NIMG-35. MACHINE LEARNING GLIOMA GRADE PREDICTION LITERATURE: A TRIPOD ANALYSIS OF REPORTING QUALITY S Merkaj, R Bahar, WR Brim, H Subramanian, T Zeevi, E Kazarian, M Lin, ... Neuro-Oncology 23 (Supplement_6), vi136-vi136, 2021 | 1 | 2021 |
| NIMG-71. Identifying clinically applicable machine learning algorithms for glioma segmentation using a systematic literature review N Tillmanns, A Lum, WR Brim, H Subramanian, M Lin, K Bousabarah, ... Neuro-Oncology 23 (Supplement_6), vi145-vi145, 2021 | 1 | 2021 |
| OTHR-12. The development of machine learning algorithms for the differentiation of glioma and brain metastases–a systematic review WR Brim, L Jekel, GC Petersen, H Subramanian, T Zeevi, S Payabvash, ... Neuro-Oncology Advances 3 (Supplement_3), iii17-iii17, 2021 | 1 | 2021 |
| Bias assessment of Artificial Intelligence papers in Glioma segmentation using TRIPOD (P14-9.005) N Tillmanns, A Lum, W Brim, H Subramanian, S Payabvash, I Ikuta, ... Neurology 98 (18 Supplement), 2022 | | 2022 |
| Machine learning approaches for automated segmentation of gliomas (P3-9.004) N Tillmanns, A Lum, W Brim, H Subramanian, S Payabvash, I Ikuta, ... Neurology 98 (18 Supplement), 2022 | | 2022 |
| Comparing Deep Learning and Classical Machine Learning Methods For Differentiating Primary CNS Lymphomas From Gliomas–A Systematic Review (P14-9.004) GC Petersen, J Shatalov, T Verma, W Brim, S Merkaj, R Bahar, ... Neurology 98 (18 Supplement), 2022 | | 2022 |
| Systematic Review of Machine Learning Models for Differentiation of Glioma from Brain Metastasis (P14-9.006) L Jekel, WR Brim, GC Petersen, S Merkaj, H Subramanian, T Zeevi, ... Neurology 98 (18 Supplement), 2022 | | 2022 |
| Neuro-Oncology Advances N Tillmanns, AE Lum, G Cassinelli, S Merkaj, T Verma, T Zeevi, L Staib, ... | | 2022 |
| world Use of AI Algorithms. Academic Radiology, Guest Editorial. Accepted 2021.-S Ebrahimian MK, S Agarwal, B Bizzo, M Elkholy, C Wald, B Allen, K Dreyer. FDA-regulated AI … JL Brim, L Jekel, H Subramanian, M Aboian, TV Merkaj, T Zeevi, L Staib, ... | | 2022 |
| NIMG-17. SYSTEMATIC REVIEW OF LITERATURE EVALUATING MACHINE LEARNING ALGORITHMS TO DEVELOP OUTCOME PREDICTION MODELS IN GLIOMA USING MOLECULAR IMAGING WITH AMINO ACID PET J Shatalov, WR Brim, H Subramanian, J Bazaar, M Johnson, M Aboian Neuro-Oncology 23 (Suppl 6), vi131, 2021 | | 2021 |
| NIMG-67. A SYSTEMATIC REVIEW ON THE DEVELOPMENT OF MACHINE LEARNING MODELS FOR DIFFERENTIATING PCNSL FROM GLIOMAS GC Petersen, J Shatalov, WR Brim, H Subramanian, M Johnson, ... Neuro-Oncology 23 (Suppl 6), vi144, 2021 | | 2021 |
| NIMG-38. MEASURING ADHERENCE TO TRIPOD OF ARTIFICIAL INTELLIGENCE PAPERS IN THE GLIOMA SEGMENTATION N Tillmanns, A Lum, WR Brim, H Subramanian, M Lin, K Bousabarah, ... Neuro-Oncology 23 (Suppl 6), vi137, 2021 | | 2021 |
Ajay MalhotraYale UniversityVerified email at yale.edu
