Copyright
©The Author(s) 2021.
Artif Intell Cancer. Apr 28, 2021; 2(2): 7-11
Published online Apr 28, 2021. doi: 10.35713/aic.v2.i2.7
Published online Apr 28, 2021. doi: 10.35713/aic.v2.i2.7
Setting | Application | Ref. |
Diagnosis | Polyp identification | [16-20] |
Polyp characterization | [21-25] | |
Prediction of invasive cancer within a polypoid lesion | [26,27] | |
Search for new diagnostic biomarkers | [10] | |
Pathologic biopsy | [28] | |
Treatment | Preoperative evaluation | [10] |
Robot-assisted surgery | [29] | |
Drug delivering in a targeted manner | [30] | |
Evaluation of drugs pharmacokinetic | [31] | |
Prediction of the rate of toxicity | [32] | |
Watson for Oncology project | [33] | |
Prognosis | Search for new prognostic biomarkers | [38] |
Evaluation of tumour-stroma ratio | [35] | |
Prediction of lymph-node metastasis | [36,37] |
- Citation: Alloro R, Sinagra E. Artificial intelligence and colorectal cancer: How far can you go? Artif Intell Cancer 2021; 2(2): 7-11
- URL: https://www.wjgnet.com/2644-3228/full/v2/i2/7.htm
- DOI: https://dx.doi.org/10.35713/aic.v2.i2.7