2025: Shubham Innani, MacLean Nasrallah, W. Robert Bell, Bhakti Baheti*, Spyridon Bakas*, AI-driven WHO 2021 classification of gliomas based only on H&E-stained slides, in Neuro-Oncology (2025): noaf189 [cite: 27]
2025: Shubham Innani, MacLean Nasrallah, W. Robert Bell, Bhakti Baheti*, Spyridon Bakas*, Interpretable artificial intelligence based determination of glioma IDH mutation status directly from histology slides, in Neuro-Oncology Advances 7.1 (2025): vdaf140 [cite: 28]
2025: Bhakti Baheti, Sunny Rai, Shubham Innani, Garv Mehdiratta, Sharath Chandra Guntuku, MacLean P. Nasrallah, and Spyridon Bakas, Multimodal Explainable AI for Prognostic Stratification of Glioblastoma Patients, In Modern Pathology (2025): 100797 [cite: 29]
2025: Katrina Collins*, Shubham Innani*, et al., Artificial Intelligence-Based Classification of Renal Oncocytic Neoplasms, in Arch Pathol Lab Med (2025): doi:10.5858/arpa.2024-0374-OA (*contributed equally) [cite: 30, 31, 32]
2024: Bhakti Baheti, Shubham Innani, MacLean P. Nasrallah, and Spyridon Bakas, Prognostic stratification of glioblastoma patients by unsupervised clustering of morphology patterns on whole slide images, In Frontiers in Neuroscience 18 (2024): 1304191 [cite: 33]
2023: Shubham Innani, Prasad Dutande, Ujjwal Baid, et al., Generative adversarial networks based skin lesion segmentation, In Nature Scientific Reports 13, no. 1 (2023): 13467 [cite: 34, 35]
2022: Fang H, et al., Shubham Innani et al., ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images, In IEEE Transactions on Medical Imaging [cite: 36]
2020: Bhakti Baheti, Shubham Innani, Suhas Gajre, Sanjay Talbar, Semantic scene segmentation in unstructured environment with modified DeepLabV3+, In Elsevier Pattern Recognition Letters [cite: 37]
Conference Proceedings
2024: Shubham Innani, MacLean Nasrallah, W. Robert Bell, Bhakti Baheti*, Spyridon Bakas*, Multi-scale Whole Slide Image Assessment Improves Deep Learning based WHO 2021 Glioma Classification, In MICCAI Workshop (COMPAYL) [cite: 39]
2022: Shubham Innani, Prasad Dutande, Bhakti Baheti, Ujjwal Baid and Sanjay Talbar, Deep Learning based Novel Cascaded Approach for Skin Lesion Analysis, In 7th CVIP [cite: 41]
2021: Bhakti Baheti, Shubham Innani, Suhas Gajre and Sanjay Talbar, Pedestrian Detection and Movement Direction Recognition with Convolutional Neural Network In 9th PReMI [cite: 42]
2021: Shubham Innani, Prasad Dutande, Bhakti Baheti, Sanjay Talbar, and Ujjwal Baid, Fuse-PN: A Novel Architecture for Anomaly Pattern Segmentation in Aerial Agricultural Images, In CVPR Workshops [cite: 43]
2020: M. T. Chiu, et al., Shubham Innani, et al., The 1st Agriculture-Vision Challenge: Methods and Results, In CVPR Workshops [cite: 44]
2020: Bhakti Baheti*, Shubham Innani*, Suhas Gajre and Sanjay Talbar, Eff-UNet: A Novel Architecture for Semantic Segmentation in Unstructured Environment, In CVPR Workshops [cite: 45, 46]
Published Abstracts
2025: Shubham Innani, W. Robert Bell, MacLean Nasrallah, Bhakti Baheti, Spyridon Bakas; Abstract 6247: Artificial intelligence predicts 2021 WHO glioma subtypes from whole slide images, Cancer Res [cite: 48, 49, 50]
2024: Shubham Innani, Bhakti Baheti, MacLean P Nasrallah, W Robert Bell, Spyridon Bakas, PATH-39: AI-based identification of glioma IDH mutational status, Neuro-Oncology [cite: 51, 52]
2024: Siddhesh Thakur, et al., Shubham Innani, et al., TMIC-60: Brats-Path: assessing heterogeneous histopathologic regions in glioblastoma, Neuro-Oncology [cite: 53, 54]
2023: Shubham Innani, Bhakti Baheti, MacLean P Nasrallah, Spyridon Bakas, Interpretable IDH classification from H&E-stained histology slides, Neuro-Oncology [cite: 55]