Chatbot assistance in precision oncology treatment decision-making.
Saved in:
| Title: | Chatbot assistance in precision oncology treatment decision-making. |
|---|---|
| Authors: | Burnette H; Vanderbilt University Medical Center and Vanderbilt Ingram Cancer Center, Nashville, TN 37232, United States., Fletcher K; Vanderbilt University School of Medicine, Nashville, TN 37232, United States., Micheel C; Vanderbilt University Medical Center and Vanderbilt Ingram Cancer Center, Nashville, TN 37232, United States., Park BH; Vanderbilt University Medical Center and Vanderbilt Ingram Cancer Center, Nashville, TN 37232, United States., Johnson DH; Ochsner Cancer Institute, New Orleans, LA 70115, United States., Cole J; Ochsner Cancer Institute, New Orleans, LA 70115, United States., Simms K; Ochsner Cancer Institute, New Orleans, LA 70115, United States., Matrana M; Ochsner Cancer Institute, New Orleans, LA 70115, United States., Johnson DB; Vanderbilt University Medical Center and Vanderbilt Ingram Cancer Center, Nashville, TN 37232, United States. |
| Source: | The oncologist [Oncologist] 2025 Oct 01; Vol. 30 (10). |
| Publication Type: | Journal Article |
| Language: | English |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9607837 Publication Model: Print Cited Medium: Internet ISSN: 1549-490X (Electronic) Linking ISSN: 10837159 NLM ISO Abbreviation: Oncologist Subsets: MEDLINE |
| Imprint Name(s): | Publication: 2022- : Oxford : Oxford University Press Original Publication: Dayton, Ohio : AlphaMed Press, c1996- |
| MeSH Terms: | Precision Medicine*/methods , Artificial Intelligence* , Medical Oncology*/methods , Neoplasms*/therapy , Neoplasms*/genetics , Clinical Decision-Making*/methods, Humans ; Decision Making ; Generative Artificial Intelligence |
| Abstract: | Artificial intelligence chatbots have shown promise in medical settings, but their ability to interpret complex molecular data is not clear. Here, we assessed 50 different patient scenarios with clinical and molecular data and found that chatbots provided mostly accurate and comprehensive recommendations, although key treatment options were omitted occasionally, and non-data driven treatments were recommended in cases with multiple mutations. (© The Author(s) 2025. Published by Oxford University Press.) |
| References: | J Immunother Cancer. 2024 May 30;12(5):. (PMID: 38816231) Front Oncol. 2024 Sep 05;14:1455413. (PMID: 39301542) J Am Med Inform Assoc. 2025 Jan 1;32(1):129-138. (PMID: 39535891) Oncologist. 2021 Nov;26(11):e1962-e1970. (PMID: 34390291) Eur J Cancer. 2024 Jul;205:114100. (PMID: 38729055) JAMA Netw Open. 2023 Nov 1;6(11):e2343689. (PMID: 37976064) JAMA Oncol. 2023 Oct 1;9(10):1459-1462. (PMID: 37615976) Cancer Discov. 2012 May;2(5):401-4. (PMID: 22588877) Digit Health. 2024 Aug 14;10:20552076241269538. (PMID: 39148811) JAMA Netw Open. 2023 Oct 2;6(10):e2336483. (PMID: 37782499) |
| Grant Information: | Susan and Luke Simons Directorship and the Van Stephenson Memorial Fund |
| Contributed Indexing: | Keywords: ChatGPT; chatbot; precision oncology |
| Entry Date(s): | Date Created: 20250927 Date Completed: 20251014 Latest Revision: 20251015 |
| Update Code: | 20251015 |
| PubMed Central ID: | PMC12517745 |
| DOI: | 10.1093/oncolo/oyaf316 |
| PMID: | 41014149 |
| Database: | MEDLINE |
Full Text 
Full Text Finder 
Nájsť tento článok vo Web of Science | Abstract: | Artificial intelligence chatbots have shown promise in medical settings, but their ability to interpret complex molecular data is not clear. Here, we assessed 50 different patient scenarios with clinical and molecular data and found that chatbots provided mostly accurate and comprehensive recommendations, although key treatment options were omitted occasionally, and non-data driven treatments were recommended in cases with multiple mutations.<br /> (© The Author(s) 2025. Published by Oxford University Press.) |
|---|---|
| ISSN: | 1549-490X |
| DOI: | 10.1093/oncolo/oyaf316 |