ChatGPT and Other Large Language Models Are Double-edged                     Swords

Shen, Yiqiu; Heacock, Laura; Elias, Jonathan; Hentel, Keith; Reig, Beatriu; Shih, George; Moy, Linda

doi:10.1148/radiol.230163

Cited by 539 publications

(361 citation statements)

References 9 publications

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“…With an increasingly aging population and accessible imaging technologies, radiology imaging volumes are only expected to rise despite persisting concerns for low-value imaging 21 . Concomitant improvements in CDS infrastructure to enhance provider accuracy of appropriate imaging orders will emerge as a major priority and the involvement of ChatGPT-like AI is already being discussed 22 .…”

Section: Discussionmentioning

confidence: 99%

Evaluating ChatGPT as an Adjunct for Radiologic Decision-Making

Rao¹,

Kim²,

Kamineni³

et al. 2023

Preprint

158

110

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BACKGROUND ChatGPT, a popular new large language model (LLM) built by OpenAI, has shown impressive performance in a number of specialized applications. Despite the rising popularity and performance of AI, studies evaluating the use of LLMs for clinical decision support are lacking. PURPOSE To evaluate ChatGPT′s capacity for clinical decision support in radiology via the identification of appropriate imaging services for two important clinical presentations: breast cancer screening and breast pain. MATERIALS AND METHODS We compared ChatGPT′s responses to the American College of Radiology (ACR) Appropriateness Criteria for breast pain and breast cancer screening. Our prompt formats included an open-ended (OE) format, where ChatGPT was asked to provide the single most appropriate imaging procedure, and a select all that apply (SATA) format, where ChatGPT was given a list of imaging modalities to assess. Scoring criteria evaluated whether proposed imaging modalities were in accordance with ACR guidelines. RESULTS ChatGPT achieved an average OE score of 1.83 (out of 2) and a SATA average percentage correct of 88.9% for breast cancer screening prompts, and an average OE score of 1.125 (out of 2) and a SATA average percentage correct of 58.3% for breast pain prompts. CONCLUSION Our results demonstrate the feasibility of using ChatGPT for radiologic decision making, with the potential to improve clinical workflow and responsible use of radiology services.

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Section: Discussionmentioning

confidence: 99%

Evaluating ChatGPT as an Adjunct for Radiologic Decision-Making

Rao¹,

Kim²,

Kamineni³

et al. 2023

Preprint

158

110

View full text Add to dashboard Cite

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“…As such, novel speech interface technologies quite naturally lag behind somewhat as far as some of the latest developments enjoyed in core speech technologies. In particular, we may reference the stunning recent developments in the audio-visual speech representations of Deepfakes [ 6 ] as well as the hugely powerful new language models used in ChatGPT [ 7 , 8 ].…”

Section: Discussionmentioning

confidence: 99%

Future Speech Interfaces with Sensors and Machine Intelligence

Denby

Csapó

Wand

2023

Sensors

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Speech is the most spontaneous and natural means of communication. Speech is also becoming the preferred modality for interacting with mobile or fixed electronic devices. However, speech interfaces have drawbacks, including a lack of user privacy; non-inclusivity for certain users; poor robustness in noisy conditions; and the difficulty of creating complex man–machine interfaces. To help address these problems, the Special Issue “Future Speech Interfaces with Sensors and Machine Intelligence” assembles eleven contributions covering multimodal and silent speech interfaces; lip reading applications; novel sensors for speech interfaces; and enhanced speech inclusivity tools for future speech interfaces. Short summaries of the articles are presented, followed by an overall evaluation. The success of this Special Issue has led to its being re-issued as “Future Speech Interfaces with Sensors and Machine Intelligence-II” with a deadline in March of 2023.

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“…Additionally, although it is collaborative-meaning conversational-it tends to make assumptions about user intent based on the information given, rather than asking clarification questions. Thus, to enhance accuracy, it is important to provide it with sufficient contextual information 8 .…”

Section: Limitationsmentioning

confidence: 99%

“…An even more serious threat to scientific integrity is the inevitable exponential rise of AIgenerated, fraudulent papers submitted to scientific journals-some of which will pass peer review and become part of the scientific literature. Equipped with the unprecedented power of AI, paper mills, which are already notorious for creating and selling fake research with fraudulent data and images, will become an even bigger threat 8 . And since AI-generated can pass plagiarism detectors, effective solutions are desperately needed to detect AI-generated content.…”

Section: Ethical Use In Researchmentioning

confidence: 99%