Medical Pre-diagnostic System
Skin cancer affects one in every 7 people throughout their lives, with 10% of those being of the malignant type which is responsible for more than 90% of skin cancer deaths. On the other hand, and more generically, skin ulcer patients typically are admitted for longer and readmitted more often than average, drawing considerable resources. The great majority of this cost and suffering can, however, be avoided if detected early in these pathologies’ development. To detect these, and also in a great number of other clinical contexts, microscopes with up to 1000x magnification are necessary but those are expensive and require specialized personnel to operate, which leads to there being few health units that can provide these services.
The challenge of MpDS project is to build a mobile solution that addresses the various needs of collecting and processing medical images in order to support diagnostic in several clinical contexts, namely: a) analysis of skin moles and ulcers and b) analysis of blood samples.
The solution aims to collect macroscopic, dermatoscopic and microscopic images of the identified pathologies, and do so with a high performance in terms of reliability and differentiation, through the coupling to a smartphone of various optical magnification peripherals.
This innovative solution will be composed by a number of integrated modules and systems, along with algorithms of image processing and supervised machine learning running locally in the smartphone and in the cloud.
The progressive introduction of mobile health solutions in the health sector has been gradually contributing for significant improvements in terms of clinical data acquisition and accessibility, especially in environments with limited healthcare resources.
The end-goal of this project is to aid the clinical decision process by simplifying the medical image acquisition process and support healthcare professionals. In turn, it will allow the optimization of resources in health units, reduce the number of in-person appointments, and reduce the back-and-forth of clinical files between local health units and specialized departments.
F3M – Information System S.A.
October 2017 to September 2019
The project (identified as POCI-01-0247-FEDER-024086) according to Portugal 2020 is co-funded by the European Structural Investment Funds (ESIF) from European Union, framed in the COMPETE 2020 (Operational Programme for Competitiveness and Internationalisation).
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