Medical vision-language models (VLMs) combine computer vision (CV) and natural
language processing (NLP) to analyze visual and textual medical data. Our paper reviews …

Diagnostic pathology, historically dependent on visual scrutiny by experts, is essential for
disease detection. Advances in digital pathology and developments in computer vision …

Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-
increasing resolution and sensitivity. However, costs, rapidly evolving technology, and lack …

While computer vision has achieved tremendous success with multimodal encoding and
direct textual interaction with images via chat-based large language models, similar …

This review article builds upon the introductory piece in our seven-part series, delving
deeper into the transformative potential of generative artificial intelligence (Gen AI) in …

The previous advancements in pathology image understanding primarily involved
developing models tailored to specific tasks. Recent studies has demonstrated that the large …

With the increasing demand for precision medicine in cancer patients, radiogenomics
emerges as a promising frontier. Radiogenomics is originally defined as a methodology for …

Interdisciplinary collaboration is crucial for addressing complex scientific challenges. Recent
advancements in large language models (LLMs) have shown significant potential in …

Deep learning models are advancing cancer research and oncology but require human
engagement to perform complex multi-step workflows. Autonomous artificial intelligence …

The advent of vision-language models fosters the interactive conversations between AI-
enabled models and humans. Yet applying these models into clinics must deal with …