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End Date Jul 2022

‘Natural Language Processing’ of Histopathology Reports – Patient and Public Involvement Survey

Cancer Type

All

Location

All

Eligibility

We are seeking individuals who have had a biopsy/surgical specimen that was reviewed by histopathology to complete our short online survey. This will include (almost) all patients that have been diagnosed with cancer.

Who is organising the research/project?

Dr Adam Levine

What is the research/project about?

Histopathology is a medical specialty in which surgical and biopsy specimens from patients are examined by doctors under the microscope to diagnose disease (including cancer) and guide further treatment.

Histopathology findings are described in text reports which contain a wealth of information of clinical and scientific value.

We seek to establish a dataset of large numbers of histopathology reports. These will be analysed using ‘Natural Language Processing’, a computer method that can automatically and accurately extract specific information from text.

By extracting information about different pathologies (e.g. subtypes of cancer) from thousands of reports, we will be able to study patterns of disease over time and characteristics that could lead to improved diagnosis and treatment of disease.

As part of our research planning, we are seeking individuals to complete a short online survey to gain views on our proposed research study, including the acceptability of the methods.

Who can take part?

We are seeking individuals who have had a biopsy/surgical specimen that was reviewed by histopathology to complete our short online survey. This will include (almost) all patients that have been diagnosed with cancer.

What does taking part involve?

Taking part involves completing a short online survey which should only take a few minutes. No personal or identifiable data is being collected.

How can you get involved?

The survey, along with further details regarding the research study, can be found here. We would be most grateful for your time and input. Thank you!         

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