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Tag: cancer

How to translate biomarker discoveries into clinical applications

Extracellular vesicles provide an exciting opportunity as a modality for non-invasive biomarkers, which may enable them to be used as biomarkers for tumour metastasis.  

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Computational pathology: Heading for personalised medicine

Computational pathology has increased applications for diagnosis, prediction of prognosis and therapy response, facilitating the movement of healthcare towards personalised medicine.

Coupled with deep learning, such tools are ever more efficient and robust within research and clinical settings.

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Machine Learning Innovation to aid Clinical Decision Making in Pathology

“A medical image alone doesn’t add value unless it is tied to a clinical decision-making process” – Jochen Lennerz

The Breast Cancer Scanning Initiative (BCSI) scans histological slides of patients with high-risk breast lesions to generate annotated images. We then apply a Machine Learning algorithm to the slides to determine whether surgery is necessary.

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Unleashing the power of digital pathology and AI for precision medicine

We’re looking back at the highlights from the Digital Pathology and AI meeting in 2018 as we anticipate this year’s Digital Pathology and AI Congress in December. This second post in our mini-series reviews Marylin Bui’s keynote presentation where she explained how the combination of Digital Pathology and Artificial Intelligence (AI) holds huge potential for patient care.

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Digital Pathology and Deep Learning: AI assisting in PD-L1 scoring

Ahead of this year’s Digital Pathology and AI Congress in December we look back at some of the highlights from last year.

First up, Michel Vandenberghe’s presentation on a new deep learning algorithm, which demonstrates the potential of artificial Intelligence (AI) to support pathologists, has been developed for PD-L1 scoring in tumour cells and immune cells in urothelial carcinoma samples.

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The Benefits of Computational Pathology

The histological assessment of human tissue has emerged as a key challenge for the detection and treatment of cancer. Many tissue sections have to be processed in order to find those that contain cancer, which can be a timely and costly process. Similarly, procedures such as immunohistochemical scoring can be problematic for cases such as ER, PR, and HER2.

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Open Letter: Richard Gallo, Professor of Dermatology UCSD

Dear Colleagues,

Over recent years, we have seen record numbers of skin cancer diagnoses around the world. Indeed, since the 1980s, incidences of melanoma, the deadliest form of cancer, have doubled. Melanoma is an aggressive form of cancer that can spread to other organs and is estimated it will kill 10,000 people in the US this year. Approximately 3 million Americans will be diagnosed with skin cancer this year in the US.

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Exploring the World’s Largest Biobanks

There are currently more than 120 biobanks worldwide. While most focus on genomic research and personalised medicine, biobanks range in size. Small operations have just a few freezers which are kept in a researcher’s laboratory, a clinical laboratory, or a pathology suite, while the larger, commercial ones support large clinical and epidemiological suites. In addition, the storage of samples tends to vary:

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