Ovarian cancer histotype classification is challenging because of substantial morphological heterogeneity and subtle subtype-specific features. This work presents a controlled evaluation of high-resolution pathology representations and slide-level aggregation methods for automated classification of five ovarian cancer...
Vijay H. Kalmani, Dr. Nagaraj V. Dharwadkar, Amol C. Adamuthe et al.· International Journal of Eng...· 0 citations
Results indicate that the proposed framework provides accurate, robust, interpretable, and reliable DR severity assessment across heterogeneous retinal image datasets.
Amol C. Adamuthe, Shilpa Bhagat, Vijay H. Kalmani· Cureus Journal of Computer S...· 0 citations
The proposed SA-RMMR framework represents an efficient and interpretable approach to customer review summarization that takes into account not only semantic relevance but also product aspects, sentiment preservation, and redundant information filtering.
Vijay H. Kalmani, Amol C. Adamuthe, P. Bagane· Discover Artificial Intellig...· 0 citations
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