Brain tumour differentiation: rapid stratified serum diagnostics via attenuated total reflection Fourier-transform infrared spectroscopy
- Submitting institution
-
Birmingham City University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11Z_OP_D0068
- Type
- D - Journal article
- DOI
-
10.1007/s11060-016-2060-x
- Title of journal
- Journal of Neuro-Oncology
- Article number
- -
- First page
- 463
- Volume
- 127
- Issue
- 3
- ISSN
- 0167-594X
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2016
- URL
-
https://link.springer.com/article/10.1007%2Fs11060-016-2060-x
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
-
- Research group(s)
-
-
- Citation count
- 57
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- Current cancer diagnostic tests observing tissue architecture and specific protein expression for specific cancers suffer from inter-observer variability, poor detection rates and occur when the patient is symptomatic. The paper presents a new method for the detection of cancer using Fourier transform infrared spectroscopy and machine learning. At the time of publication, this was the largest study on serum mid-infrared spectroscopy for cancer research. It demonstrated for the first time that infrared light can be used to detect various forms of cancers. The paper has been referenced 79 times, including high-profile publications such as DOI:10.1039/C7AN01871A, DOI:10.1080/10408363.2017.1414142, and DOI:10.1039/C6AN01888B.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
