Introduction: The emergence of artificial intelligence (AI) has presented several opportunities to ease human work. AI applications are available for almost every domain of life. A new technology, Chat Generative Pre-Trained Transformer (ChatGPT), was introduced by OpenAI in November 2022, and has become a topic of discussion across the world. ChatGPT-3 has brought many opportunities, as well as ethical and privacy considerations. ChatGPT is a large language model (LLM) which has been trained on the events that happened until 2021. The use of AI and its assisted technologies in scientific writing is against research and publication ethics. Therefore, policies and guidelines need to be developed over the use of such tools in scientific writing. The main objective of the present study was to highlight the use of AI and AI assisted technologies such as the ChatGPT and other chatbots in the scientific writing and in the research domain resulting in bias, spread of inaccurate information and plagiarism.
Methodology: Experiments were designed to test the accuracy of ChatGPT when used in research and academic writing.
Results: The information provided by ChatGPT was inaccurate and may have far-reaching implications in the field of medical science and engineering. Critical thinking should be encouraged among researchers to raise awareness about the associated privacy and ethical risks.
Conclusions: Regulations for ethical and privacy concerns related to the use of ChatGPT in academics and research need to be developed.
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http://dx.doi.org/10.3855/jidc.18738 | DOI Listing |
JMIR Med Educ
January 2025
Department of Women's and Children's Health, Uppsala University, Uppsala, Sweden.
Background: Patients in the United States have recently gained federally mandated, free, and ready electronic access to clinicians' computerized notes in their medical records ("open notes"). This change from longstanding practice can benefit patients in clinically important ways, but studies show some patients feel judged or stigmatized by words or phrases embedded in their records. Therefore, it is imperative that clinicians adopt documentation techniques that help both to empower patients and minimize potential harms.
View Article and Find Full Text PDFClin Drug Investig
January 2025
Medical Science Department, Shionogi & Co., Ltd., Osaka, Japan.
Background: Anti-obesity medications are recommended for patients who do not achieve and maintain weight loss despite lifestyle interventions. S-309309 is a novel oral inhibitor of monoacylglycerol O-acyltransferase 2 being developed as a treatment for obesity.
Objective: The objective of the study was to investigate the safety, clinical pharmacology, pharmacokinetics and pharmacodynamic biomarker of S-309309.
Jpn J Ophthalmol
January 2025
Department of Ophthalmology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
Purpose: To determine whether corneal biomechanical parameters can predict ectasia progression.
Study Design: Retrospective observational study.
Methods: The baseline corneal biomechanical parameters of 64 eyes of 41 young patients (age, < 25 years at the first visit) who were diagnosed with keratoconus (KC) or suspected KC at Osaka University Hospital and followed up for more than two years were reviewed.
Front Robot AI
January 2025
Department of Computer Science, Faculty of Engineering (LTH), Lund University, Lund, Sweden.
When developing general-purpose robot software components, we often lack complete knowledge of the specific contexts in which they will be executed. This limits our ability to make predictions, including our ability to detect program bugs statically. Since running a robot is an expensive task, finding errors at runtime can prolong the debugging loop or even cause safety hazards.
View Article and Find Full Text PDFTransl Lung Cancer Res
December 2024
Department of Pathology, Aberdeen Royal Infirmary, Aberdeen, UK.
Background: Anti-angiogenic agents, such as nintedanib and ramucirumab, when combined with docetaxel, are subsequent treatment options in patients with non-small cell lung cancer (NSCLC) who have failed on first-line chemotherapy or immunochemotherapy. However, to date, there are no validated predictive biomarkers for efficacy of anti-angiogenic therapies in this setting. The aim of this study was to explore whether genetic or genomic markers, alone or combined with clinical covariates, could be used to predict overall survival (OS) in patients with NSCLC who are eligible for treatment with nintedanib plus docetaxel.
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