Assessment of Primary Human Liver Cancer Cells by Artificial Intelligence-Assisted Raman Spectroscopy
Concetta Esposito, Mohammed Janneh, Sara Spaziani, Vincenzo Calcagno, Mario Luca Bernardi, Martina Iammarino, Chiara Verdone, Maria Tagliamonte, Luigi Buonaguro, Marco Pisco, Lerina Aversano, Andrea Cusano · 2023
Read Assessment of Primary Human Liver Cancer Cells by Artificial Intelligence-Assisted Raman Spectroscopy by Concetta Esposito, Mohammed Janneh, Sara Spaziani, Vincenzo Calcagno, Mario Luca Bernardi, Martina Iammarino, Chiara Verdone, Maria Tagliamonte, Luigi Buonaguro, Marco Pisco, Lerina Aversano, Andrea Cusano (2023) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-10670489.txt.
Description
Concetta Esposito and co-authors test a light based method in a 2023 paper on liver cancer cells. The method shines light on cells and reads how the light scatters, a fingerprint of the cell's makeup. Paired with AI, those fingerprints might tell tumor cells from healthy ones without stains or labels.
Cells came from removed tumors and from nearby healthy tissue of the same patients, forty of each kind. Shape and light readings were taken first. Three learning methods, from classic models to neural nets, were then trained on the readings. All three sorted the cells well, hinting at a fast aid for spotting cancer in tissue samples.
Catalog record
| CREATOR | Concetta Esposito, Mohammed Janneh, Sara Spaziani, Vincenzo Calcagno, Mario Luca Bernardi, Martina Iammarino, Chiara Verdone, Maria Tagliamonte, Luigi Buonaguro, Marco Pisco, Lerina Aversano, Andrea Cusano |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 46 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |