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Tag: ai

How will Ground Truth Colour Standardisation yield the benefits of AI in Medical Imaging?

The essence of colour management is to ensure that the original target translates through a digital pathway so that the output images are exactly the same colour as the original.

When applied to medical imaging, and considering all the specific stains used in pathology, colour management becomes important. Particular coloured stains bind specific structures of cells in tissue to confer visualisation of diagnostic information. Without translating the colour through the digital pathway correctly, you lose the aspect of diagnostic information, which comes from specific colours.

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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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Reshaping drug discovery with deep learning and polypharmacology

Cyclica is a Toronto-based biotech that leverages artificial intelligence and computational biophysics to reshape the drug discovery process. We spoke to their Chief Scientific Officer Andreas Windemuth.

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Bridging the gap between pathologist and algorithm

Could AI replace pathologists? As we look forward to the 6th Digital Pathology and AI Congress: Europe on the 5th – 6th December 2019, we look back at Dr Hamid Tizhoosh’s keynote presentation from last year.

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Pixel analysis: the new era of digital pathology

Professor David Snead is leading the implementation of digital pathology for Coventry and Warwickshire Pathology Services and directs one of the five Government funded centres in the UK pioneering AI and image diagnostics integration. His main research interests lie in extending the capability of digital pathology for routine diagnostic use and the advancement and deployment of computer assisted diagnostic algorithms. In this third highlight from the conference we revisit Professor Snead’s presentation to get a clinical perspective on how deep learning and artificial intelligence (AI) are set to play an increasing role in daily practice.

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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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Will the intersection of blockchain and AI inspire the Pharma R&D Renaissance?

Global Engage spoke to Scott Kahn ahead of the 3rdGlobal Pharma R&D Informatics and AI Congress. Scott is the CIO of Luna PBC, the entity that manages LunaDNA: a community-owned data-sharing resource. Their conversation was recorded as a podcast, which can be found here.

This is the second half of that conversation, where Scott discusses the challenges of distributive ledger technologies such as Blockchain, and their intersection with AI for Pharma R&D.

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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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