An Open-Source BioMEMS Platform for Generalized Early Cancer Detection
Cancer remains one of the most pressing challenges for humanity, with early detection significant for improving survival rates. Open-source initiatives have revolutionized various fields by fostering collaboration, broadening impact, and democratizing access to resources. We propose to expand this ethos to cancer research, introducing a versatile biosensing framework developed using open-source tools only. This biosensor is capable of detecting diverse types of cancer simultaneously, or detecting a single type with enhanced sensitivity. To validate the platform, a proof-of-concept design is presented, and limitations of the current open-source ecosystem are discussed.
Authors
- J. P. Nunes (ORCID: https://orcid.org/0000-0002-1716-5165)
- João Frischenbruder Sulzbach
- Lucca Reinehr Silva
- Thales Vieira e Silva Lobo de Almeida
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Universidade Federal do Rio Grande do Sul (BR)
- Universidade Estadual Paulista (Unesp) (BR)
Publication Details
- Published
- 2024-09-02
- DOI
- https://doi.org/10.1109/inscit62583.2024.10693413
- Citations
- 1
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.12