Foundation models are a novel type of artificial intelligence algorithms, in which models are pretrained at scale on unannotated data and fine-tuned for a myriad of downstream tasks, such as ...generating text. This study assessed the accuracy of ChatGPT, a large language model (LLM), in the ophthalmology question-answering space.
Evaluation of diagnostic test or technology.
ChatGPT is a publicly available LLM.
We tested 2 versions of ChatGPT (January 9 "legacy" and ChatGPT Plus) on 2 popular multiple choice question banks commonly used to prepare for the high-stakes Ophthalmic Knowledge Assessment Program (OKAP) examination. We generated two 260-question simulated exams from the Basic and Clinical Science Course (BCSC) Self-Assessment Program and the OphthoQuestions online question bank. We carried out logistic regression to determine the effect of the examination section, cognitive level, and difficulty index on answer accuracy. We also performed a post hoc analysis using Tukey's test to decide if there were meaningful differences between the tested subspecialties.
We reported the accuracy of ChatGPT for each examination section in percentage correct by comparing ChatGPT's outputs with the answer key provided by the question banks. We presented logistic regression results with a likelihood ratio (LR) chi-square. We considered differences between examination sections statistically significant at a
value of < 0.05.
The legacy model achieved 55.8% accuracy on the BCSC set and 42.7% on the OphthoQuestions set. With ChatGPT Plus, accuracy increased to 59.4% ± 0.6% and 49.2% ± 1.0%, respectively. Accuracy improved with easier questions when controlling for the examination section and cognitive level. Logistic regression analysis of the legacy model showed that the examination section (LR, 27.57;
= 0.006) followed by question difficulty (LR, 24.05;
< 0.001) were most predictive of ChatGPT's answer accuracy. Although the legacy model performed best in general medicine and worst in neuro-ophthalmology (
< 0.001) and ocular pathology (
= 0.029), similar post hoc findings were not seen with ChatGPT Plus, suggesting more consistent results across examination sections.
ChatGPT has encouraging performance on a simulated OKAP examination. Specializing LLMs through domain-specific pretraining may be necessary to improve their performance in ophthalmic subspecialties.
Proprietary or commercial disclosure may be found after the references.
Introduction: Oncological patients face numerous challenges throughout their cancer journey while navigating complex medical information. The advent of AI-based conversational models like ChatGPT ...(San Francisco, OpenAI) represents an innovation in oncological patient management. Methods: We conducted a comprehensive review of the literature on the use of ChatGPT in providing tailored information and support to patients with various types of cancer, including head and neck, liver, prostate, breast, lung, pancreas, colon, and cervical cancer. Results and Discussion: Our findings indicate that, in most instances, ChatGPT responses were accurate, dependable, and aligned with the expertise of oncology professionals, especially for certain subtypes of cancers like head and neck and prostate cancers. Furthermore, the system demonstrated a remarkable ability to comprehend patients’ emotional responses and offer proactive solutions and advice. Nevertheless, these models have also showed notable limitations and cannot serve as a substitute for the role of a physician under any circumstances. Conclusions: Conversational models like ChatGPT can significantly enhance the overall well-being and empowerment of oncological patients. Both patients and healthcare providers must become well-versed in the advantages and limitations of these emerging technologies.
Generative Pretrained Transformer, often known as GPT, is an innovative kind of Artificial Intelligence (AI) which can produce writing that seems to have been written by a person. OpenAI created this ...AI language model called ChatGPT. It is built using the GPT architecture and is trained on a large corpus of text data to respond to natural language inquiries that resemble a person’s requirements. This technology has lots of applications in healthcare. The need for accurate and current data is one of the major obstacles to adopting ChatGPT in healthcare. GPT must have access to precise and up-to-date medical data to provide trustworthy suggestions and treatment options. It might be accomplished by ensuring that the data used by GPT is received from reliable sources and that the data is updated regularly. Since sensitive medical information would be involved, it will also be crucial to consider privacy and security issues while utilising GPT in the healthcare industry. This paper briefs about ChatGPT and its need for healthcare, its significant Work Flow Dimensions and typical features of ChatGPT for the Healthcare domain. Finally, it identified and discussed significant applications of ChatGPT for healthcare. ChatGPT can comprehend the conversational context and provide contextually appropriate replies. Its effectiveness as a conversational AI tool makes it useful for chatbots, virtual assistants, and other applications. However, we see many limitations in medical ethics, data interpretation, accountability and other issues related to the privacy. Regarding specialised tasks like text creation, language translation, text categorisation, text summarisation, and creating conversation systems, ChatGPT has been pre-trained on a large corpus of text data, and somewhat satisfactory results can be expected. Moreover, it can also be utilised for various Natural Language Processing (NLP) activities, including sentiment analysis, part-of-speech tagging, and named entity identification.
•Generative Pretrained Transformer (GPT) can produce writing that a person has written.•Open Artificial Intelligence (AI) created this AI language model called ChatGPT.•Paper briefs ChatGPT, its need for healthcare, features and its significant Work Flow Dimensions.•This technology has many healthcare applications that better support patient care, research and planning, and treatment options, but with some limitations.•Paper identifies and discusses significant applications of ChatGPT for healthcare.
To evaluate the accuracy of ChatGPT references in scientific writing relevant to head and neck surgery.
Five commonly researched keywords relevant to head and neck surgery were selected ...(osteoradionecrosis of the jaws, oral cancer, adjuvant therapy for oral cancer, TORS, and free flap reconstruction in oral cancer). The AI chatbot was then asked to provide ten complete citations for each of the keywords. Two independent authors reviewed the results for accuracy and assigned each article a numerical score based on pre-selected criteria.
Among 50 total references provided by ChatGPT, only five (10 %) were found to have the correct title, journal, authors, year of publication, and DOI. Merely 14 % of the presented references had correct DOI. References regarding free flap reconstruction for oral cancer were the least accurate from all the five categories, with no correct DOI. Complete inter-rater agreement was noted while evaluating the citations.
Only 10 % of the articles provided by ChatGPT, relevant to head and neck surgery, were correct. A high degree of academic hallucination was noted.
•ChatGPT produced only 5 (10 %) correct references regarding head and neck surgery among 50 references.•Among reference title, journal, author, year of publication, and DOI, DOI had the lowest accuracy at 14 %.•While accuracy did not differ significantly related to the topic, free flap reconstruction yielded no correct references.
The present study aims to unpack the potentials of ChatGPT for language learning based on students’ perspectives. Specifically, this study scrutinizes language learning needs that can be fulfilled by ...ChatGPT, potential benefits of ChatGPT, and limitations of ChatGPT for language education. Drawing on exploratory case study, this study involves 18 language students majoring in English education and linguistic studies from two public universities in Indonesia. The findings of semi-structured interviews and FGD reveal that ChatGPT shows great promise as a digital platform that can support personalize learning, stimulate authentic interactions, and boost student productivity. This study suggests that students can gain several advantages from ChatGPT to support their language learning, such as enhancing their writing skills (e.g., translation, paraphrasing, outlining, and receiving assistance with grammar and syntax), improving vocabulary acquisition, providing learning materials, and serving as conversation partner. However, students might encounter certain challenges when using ChatGPT for language learning, such as the risk of cheating and plagiarism, inaccurate responses, and ambiguous information which can lead to confusion and misunderstanding. This study offers fruitful insights for language education stakeholders (especially teachers and students) to enhance their digital competencies specifically related to the use of AI tools in language education.
•The potential benefits for companies of adopting ChatGPT, a popular chatbot built on a large-scale transformer.•To carefully analyze its use cases and restrictions, as well as its strengths and ...disadvantages.•ChatGPT requires training data that is particular to the business domain and might produce erroneous and ambiguous findings.•To close a gap in the literature by outlining ChatGPT's potential benefits for businesses, analyzing its strengths and limits, and offering insights into how organizations might use ChatGPT's capabilities to enhance their operations.
The study addresses the potential benefits for companies of adopting ChatGPT, a popular chatbot built on a large-scale transformer-based language model known as a generative pre-trained transformer (GPT). Chatbots like ChatGPT may improve customer service, handle several client inquiries at once, and save operational costs. Moreover, ChatGPT may automate regular processes like order tracking and billing, allowing human employees to focus on more complex and strategic responsibilities. Nevertheless, before deploying ChatGPT, enterprises must carefully analyze its use cases and restrictions, as well as its strengths and disadvantages. ChatGPT, for example, requires training data that is particular to the business domain and might produce erroneous and ambiguous findings. The study identifies areas of deployment of ChatGPT's possible benefits in enterprises by drawing on the literature that is currently accessible on ChatGPT, massive language models, and artificial intelligence. Then, using the PSI (Preference Selection Index) and COPRAS (Complex Proportional Assessment) approaches, potential advantages are taken into account and prioritized. By highlighting current trends and possible advantages in the industry, this editorial seeks to provide insight into the present state of employing ChatGPT in enterprises and research. ChatGPT may also learn biases from training data and create replies that reinforce those biases. As a result, enterprises must train and fine-tune ChatGPT to specific operations, set explicit boundaries and limitations for its use, and implement appropriate security measures to avoid malicious input. The study highlights the research gap in the dearth of literature by outlining ChatGPT's potential benefits for businesses, analyzing its strengths and limits, and offering insights into how organizations might use ChatGPT's capabilities to enhance their operations.
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Figure: Illustration of benefits parameters scores
Figure: Illustration of sub-benefits parameters scores
How does ChatGPT, and other forms of Generative Artificial Intelligence (GenAI) affect the way we have been conducting—and evaluating—academic research, teaching, and business practice? What are the ...implications for the theory and practice of marketing? What are the opportunities and threats, and what are some interesting avenues for future research? This editorial aims to kick off an initial discussion and stimulate research that will help us better understand how the marketing field can fully exploit the potential of GenAI and effectively cope with its challenges.
The current technological advancement follows a pattern of both disruptive and gradual changes. The field of communication is currently the most extensively utilized technology. The rapid development ...of AI has enabled those without a background in computer coding or specialized health knowledge to utilize this technology, which gives rise to numerous issues. This phenomenon elicits curiosity and engenders debate among the general public, scholars, healthcare providers, and researchers in the health industry. Utilizing AI in the composition of scientific publications necessitates explicit norms and regulations, a robust validation procedure, and effective collaboration between AI systems and human expertise. Ensuring transparency and acknowledgment of AI usage is crucial to maintaining human researchers' accountability for the ultimate outcomes of their research.
ChatGPT and the future of impact assessment Khan, Mehreen; Chaudhry, Muhammad Nawaz; Ahsan, Muhammad ...
Environmental science & policy,
July 2024, 2024-07-00, Letnik:
157
Journal Article
Recenzirano
Like all other fields, Artificial Intelligence (AI) is expected to affect the Impact Assessment (IA) systems worldwide. This study explores the opinions and concerns of international IA experts ...regarding how ChatGPT may change the future of IA in terms of the benefits and threats it may pose to IA. Twenty-five semi-structured interviews were conducted with IA experts including consultants, regulators, and academics. The majority of the interviewees were of the view that ChatGPT will help reduce the time and effort required for preliminary data collection and will improve the report quality in terms of formatting and sentence structure etc. However, a number of interviewees also feared that the quality of data in reports and public involvement in IA process may be compromised, chances of plagiarism and bias may increase, and the quality of IA graduates produced by academic institutions may deteriorate. The majority of the experts were afraid that ChatGPT will pose more threats to IA compared to the benefits it may offer. The policymakers, while keeping all these concerns in mind, need to formulate laws, rules, and guidelines regarding the use of ChatGPT in IA in their respective areas as suggested by the interviewees. Future studies may be conducted to evaluate and compare the use of different types of chatbots such as Google’s Bard or Microsoft’s Bing in IA. Additionally, AI related laws and guidelines drafted by IA systems across the globe and their implementation may be evaluated a couple of years later.
•Experts are concerned about the use of Artificial Intelligence in Impact Assessment•ChatGPT may pose more threats to Impact Assessment compared to the benefits•Chances of plagiarism may increase•Report quality in terms of structure and grammar may improve
