14 March 2025
Researchers at King’s have launched a first-of-its-kind dashboard that collates and drills down into more than a thousand AI and cancer studies, providing a wide-ranging overview of AI’s increasingly important role in tackling the disease.
The [AI in Histopathology Explorer (HistoPathExpo)](https://www.histopathexpo.ai/) is a comprehensive online library of published studies focusing on AI tools used in cancer diagnostics and prognosis through microscopic images. Its advanced search functionality allows users to learn about new AI tools and their applications for a variety of tasks related to cancer.
The flexibility of the dashboard also holds potential for stakeholders ranging from researchers looking to understand more about AI tools, doctors making clinical decisions, and policymakers investigating trends.
Histopathology is a widespread technique used in cancer where clinicians examine microscopic tissue samples to diagnose and learn more about a cancer. AI can analyse a huge amount of images to automatically identify signs of cancer indications and help doctors make the right treatment decisions faster and more accurately. Over the last ten years, researchers have developed numerous advanced AI tools showing their potential to improve the precision and efficiency of cancer diagnosis and detection from histopathology images. The rapid pace of research, with almost a paper published daily, has led to a vast and complex landscape of AI tools.
Recognising the rapid growth of AI research in cancer and the need for a centralized resource, Dr Heba Sailem, Senior Lecturer of Biomedical AI and Data Science at King’s, and her team analysed more than 1,400 academic studies and created HistoPathExpo to make the information more easily accessible. Dr Sailem published a paper in the journal [npj Digital Medicine](https://www.nature.com/articles/s41746-025-01524-2?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20250312&utm_content=10.1038/s41746-025-01524-2) that describes the development of the dashboard and elaborates on how it allows users to generate customised search results and compare and evaluate various AI applications, such as whether a tissue sample is normal or malignant, the cancer subtype, the severity of cancer and the likelihood of a patient responding to treatment and even if the patient has certain genetic mutations that can guide their treatment options.
> We are excited by the potential of AI to transform cancer patient treatment worldwide. We believe HistoPathExpo will play a crucial role in accelerating the development and translation of AI methods to patient care."
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> Dr Heba Sailem, Senior Lecturer of Biomedical AI and Data Science and Wellcome Career Development Fellow.
The study revealed key insights into the focus of AI research, with breast and colorectal cancers making up 40% of all studies. For example, since 2015, more than 300 papers have been published focusing on AI in breast cancers with an average accuracy of 90%, demonstrating the great potential in these areas. HistoPathExpo reveals a critical need for increased research focus on AI applications in other cancers, such as bladder and pancreatic cancers, helping policy and decision-makers to identify trends and signalling areas to focus on.
Due to the fact that histopathology is a globally adopted and standardised technique, AI tools are increasingly being tested on diverse patient populations from a wide range of countries. HistoPathExpo serves as a centralised hub of AI tools, publicly available code and imaging datasets from countries in North America, Europe, Asia and more. As research continues to be carried out globally, Dr Sailem and her team, driven by their commitment to developing innovative AI solutions for improving cancer patient treatment, envision HistoPathExpo as a constantly evolving platform as global research progresses.
The dashboard helps clinicians stay at the forefront of AI in cancer diagnostics. They can quickly identify the latest research, compare different AI tools, and understand emerging trends, which is crucial for informing future research directions and potential collaborations.