Vision-language models for medical report generation and visual question answering: A review

I Hartsock, G Rasool - Frontiers in Artificial Intelligence, 2024 - frontiersin.org
Medical vision-language models (VLMs) combine computer vision (CV) and natural
language processing (NLP) to analyze visual and textual medical data. Our paper reviews …

Multimodal data integration for oncology in the era of deep neural networks: a review

A Waqas, A Tripathi, RP Ramachandran… - Frontiers in Artificial …, 2024 - frontiersin.org
Cancer research encompasses data across various scales, modalities, and resolutions, from
screening and diagnostic imaging to digitized histopathology slides to various types of …

SeNMo: a self-normalizing deep learning model for enhanced multi-omics data analysis in oncology

A Waqas, A Tripathi, S Ahmed, A Mukund… - Cancer …, 2024 - aacrjournals.org
Multi-omics research has enhanced our understanding of cancer heterogeneity and
progression. Investigating molecular data through multi-omics approaches is crucial for …

Embedding-based Multimodal Learning on Pan-Squamous Cell Carcinomas for Improved Survival Outcomes

A Waqas, A Tripathi, P Stewart, M Naeini… - arXiv preprint arXiv …, 2024 - arxiv.org
Cancer clinics capture disease data at various scales, from genetic to organ level. Current
bioinformatic methods struggle to handle the heterogeneous nature of this data, especially …

Digital pathology and multimodal learning on oncology data

A Waqas, J Naveed, W Shahnawaz… - BJR| Artificial …, 2024 - academic.oup.com
Cancer presents a complex tapestry of biological, clinical, and molecular characteristics that
collectively influence its diagnosis, progression, and treatment. This review paper delves …