Artificial intelligence (AI) has been commoditized. It has evolved from a specialty resource to
a readily accessible tool for cancer researchers. AI-based tools can boost research …

Quantitative evaluation of tissue images is crucial for computational pathology (CPath) tasks,
requiring the objective characterization of histopathological entities from whole-slide images …

The technological progress in artificial intelligence (AI) has massively accelerated since
2022, with far-reaching implications for oncology and cancer research. Large language …

In recent years, the diagnosis of gliomas has become increasingly complex. Analysis of
glioma histopathology images using artificial intelligence (AI) offers new opportunities to …

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range
of tasks, is advancing healthcare. It promotes the development of healthcare artificial …

Advanced multimodal large language models (LLM), such as GPT-4V (ision) and Gemini
Ultra, have shown promising results in the diagnosis of complex pathological conditions …

Histopathology is considered the reference standard for diagnosing the presence and
nature of many malignancies, including cancer. However, analyzing tissue samples and …

Large language models (LLMs) are transformer-based neural networks that can provide
human-like responses to questions and instructions. LLMs can generate educational …

With the significant advancements of Large Language Models (LLMs) in the field of Natural
Language Processing (NLP), the development of image-text multimodal models has …

The rapid development of artificial intelligence has constantly reshaped the field of
intelligent healthcare and medicine. As a vital technology, multimodal learning has …