ChatGPT in medicine: Correspondence DOI Creative Commons
Hinpetch Daungsupawong, Viroj Wiwanitkit

International Journal of Surgery, Journal Year: 2024, Volume and Issue: 110(11), P. 7385 - 7385

Published: July 8, 2024

aPrivate Academic Consultant, Phonhong, Lao People's Democratic Republic bDepartment of Research Analytics, Saveetha Dental College and Hospitals, Institute Medical Technical Sciences University India We confirm that we have read the Journal's position on issues involved in ethical publication affirm this report is consistent with those guidelines Sponsorships or competing interests may be relevant to content are disclosed at end article. Published online ■ *Correspondence; Private Republic. Email: [email protected] (H. Daungsupawong). This an open access article distributed under Creative Commons Attribution-ShareAlike License 4.0, which allows others remix, tweak, build upon work, even for commercial purposes, as long author credited new creations licensed identical terms. http://creativecommons.org/licenses/by-sa/4.0/

Language: Английский

Impact of generative artificial intelligence models on the performance of citizen data scientists in retail firms DOI
Rabab Ali Abumalloh, Mehrbakhsh Nilashi, Keng‐Boon Ooi

et al.

Computers in Industry, Journal Year: 2024, Volume and Issue: 161, P. 104128 - 104128

Published: July 21, 2024

Language: Английский

Citations

5
MyEcoReporter: a prototype for artificial intelligence-facilitated pollution reporting DOI Creative Commons
Weihsueh A. Chiu, Galen Newman, Garett Sansom

et al.

Journal of Exposure Science & Environmental Epidemiology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 20, 2025

Language: Английский

Citations

0
Prompt Design through ChatGPT’s Zero-Shot Learning Prompts: A Case of Cost-Sensitive Learning on a Water Potability Dataset DOI Creative Commons
Kokisa Phorah, Malusi Sibiya, Mbuyu Sumbwanyambe

et al.

Informatics, Journal Year: 2024, Volume and Issue: 11(2), P. 27 - 27

Published: April 28, 2024

Datasets used in AI applications for human health require careful selection. In healthcare, machine learning (ML) models are fine-tuned to reduce errors, and our study focuses on minimizing errors by generating code snippets cost-sensitive using water potability datasets. Water ensures safe drinking through various scientific methods, with approach ML algorithms prediction. We preprocess data ChatGPT-generated aim demonstrate how zero-shot prompts ChatGPT can produce reliable that cater learning. Our dataset is sourced from Kaggle. compare model performance metrics of logistic regressors gradient boosting classifiers without additional fine-tuning check the accuracy. Other classifier compared results top 5 authors Kaggle scoreboard. Cost-sensitive crucial domains like healthcare prevent misclassifications serious consequences, such as type II assessment.

Language: Английский

Citations

0
ChatGPT in medicine: Correspondence DOI Creative Commons
Hinpetch Daungsupawong, Viroj Wiwanitkit

International Journal of Surgery, Journal Year: 2024, Volume and Issue: 110(11), P. 7385 - 7385

Published: July 8, 2024

aPrivate Academic Consultant, Phonhong, Lao People's Democratic Republic bDepartment of Research Analytics, Saveetha Dental College and Hospitals, Institute Medical Technical Sciences University India We confirm that we have read the Journal's position on issues involved in ethical publication affirm this report is consistent with those guidelines Sponsorships or competing interests may be relevant to content are disclosed at end article. Published online ■ *Correspondence; Private Republic. Email: [email protected] (H. Daungsupawong). This an open access article distributed under Creative Commons Attribution-ShareAlike License 4.0, which allows others remix, tweak, build upon work, even for commercial purposes, as long author credited new creations licensed identical terms. http://creativecommons.org/licenses/by-sa/4.0/

Language: Английский

Citations

0