Novel imaging platform for early and precise cancer diagnosis

Novel imaging platform for early and precise cancer diagnosis Regina Gumenyuk, Adjunct Professor at Tampere University, is exploring a novel imaging platform for early and precise cancer diagnosis. Read more about this exciting innovation here. Cancer is the second leading killer in the world, behind cardiovascular diseases. Survival rates are highly dependent on early detection, the accuracy of lesion stage diagnosis, and state-of-the-art treatment methods. Despite tremendous worldwide efforts to improve the diagnosis and treatment of cancer, current approaches are unable to shift the negative paradigm in terms of mortality rate. One of the main reasons is cancer’s cunning and unpredictability.

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Publication Details

Journal
Open Access Government
Published
2025-04-08
DOI
https://doi.org/10.56367/oag-046-11893
Primary Topic
Radiomics and Machine Learning in Medical Imaging
Type
article
Field-Weighted Citation Impact
0.00
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article

Novel imaging platform for early and precise cancer diagnosis

Regina Gumenyuk
Open Access Government
Radiomics and Machine Learning in Medical Imaging
article

Novel imaging platform for early and precise cancer diagnosis

Regina Gumenyuk
article en

Abstract

Novel imaging platform for early and precise cancer diagnosis Regina Gumenyuk, Adjunct Professor at Tampere University, is exploring a novel imaging platform for early and precise cancer diagnosis. Read more about this exciting innovation here. Cancer is the second leading killer in the world, behind cardiovascular diseases. Survival rates are highly dependent on early detection, the accuracy of lesion stage diagnosis, and state-of-the-art treatment methods. Despite tremendous worldwide efforts to improve the diagnosis and treatment of cancer, current approaches are unable to shift the negative paradigm in terms of mortality rate. One of the main reasons is cancer’s cunning and unpredictability.

Open Access GovernmentVol. 46(1)
Tampere University (FI)
Openalex Percentile: Top 89%
Radiomics and Machine Learning in Medical Imaging
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