Readability of Arabic Medicine Information Leaflets: A Machine Learning Approach

Alotaibi, Sihaam; Al-Yahya, Maha; Al‐Khalifa, Hend S.; Alageel, Sinaa; Abanmy, Norah O.

doi:10.1016/j.procs.2016.04.017

Cited by 8 publications

(4 citation statements)

References 12 publications

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“…It remains unclear why there exists a discrepancy between Readable.com versus AI rating of readability. The effectiveness of classifying a text into readability levels depends on various factors, including the selection of the dataset, the choice of algorithm, and the selection of features to be extracted from the text [ 18 ]. AI algorithms may possess unique qualities that distinguish them from conventional readability tools that have been in use for a significant period.…”

Section: Discussionmentioning

confidence: 99%

ChatGPT's Ability to Assess Quality and Readability of Online Medical Information: Evidence From a Cross-Sectional Study

Golan,

Ripps,

Reddy

et al. 2023

Cureus

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Introduction Artificial Intelligence (AI) platforms have gained widespread attention for their distinct ability to generate automated responses to various prompts. However, its role in assessing the quality and readability of a provided text remains unclear. Thus, the purpose of this study is to evaluate the proficiency of the conversational generative pre-trained transformer (ChatGPT) in utilizing the DISCERN tool to evaluate the quality of online content regarding shock wave therapy for erectile dysfunction. Methods Websites were generated using a Google search of “shock wave therapy for erectile dysfunction” with location filters disabled. Readability was analyzed using Readable software ( Readable.com , Horsham, United Kingdom). Quality was assessed independently by three reviewers using the DISCERN tool. The same plain text files collected were inputted into ChatGPT to determine whether they produced comparable metrics for readability and quality. Results The study results revealed a notable disparity between ChatGPT's readability assessment and that obtained from a reliable tool, Readable.com (p<0.05). This indicates a lack of alignment between ChatGPT's algorithm and that of established tools, such as Readable.com . Similarly, the DISCERN score generated by ChatGPT differed significantly from the scores generated manually by human evaluators (p<0.05), suggesting that ChatGPT may not be capable of accurately identifying poor-quality information sources regarding shock wave therapy as a treatment for erectile dysfunction. Conclusion ChatGPT’s evaluation of the quality and readability of online text regarding shockwave therapy for erectile dysfunction differs from that of human raters and trusted tools. Therefore, ChatGPT's current capabilities were not sufficient for reliably assessing the quality and readability of textual content. Further research is needed to elucidate the role of AI in the objective evaluation of online medical content in other fields. Continued development in AI and incorporation of tools such as DISCERN into AI software may enhance the way patients navigate the web in search of high-quality medical content in the future.

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Section: Discussionmentioning

confidence: 99%

ChatGPT's Ability to Assess Quality and Readability of Online Medical Information: Evidence From a Cross-Sectional Study

Golan,

Ripps,

Reddy

et al. 2023

Cureus

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“…What's more, it gives the ML techniques a full play as this approach is more sophisticated at learning the regularities at training phase, so as to be more accurate at approximating the human results at testing phase [34]. In many studies, when employing human to label, researchers would disregard features of human labelers in ML approach [33][34][35][36]. Even though they have described the demographic features or education background of the human labelers in their studies, these features were not taken into consideration in the analysis or discussion.…”

Section: Machine Learning For Readability Estimationmentioning

confidence: 99%

Combining Readability Formulas and Machine Learning for Reader-oriented Evaluation of Online Health Resources

Liu

Lin

et al. 2021

IEEE Access

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Websites are rich resources for the public to access health information, and readability ensures whether the information can be comprehended. Apart from the linguistic features originated in traditional readability formulas, the reading ability of an individual is also influenced by other factors such as age, morbidities, cultural and linguistic background. This paper presents a reader-oriented readability assessment by combining readability formula scores with machine learning techniques, while considering reader background. Machine learning algorithms are trained by a dataset of 7 readability formula scores for 160 health articles in official health websites. Results show that the proposed assessment tool can provide a reader-oriented assessment to be more effective in proxy the health information readability. The key significance of the study includes its reader centeredness, which incorporates the diverse backgrounds of readers, and its clarification of the relative effectiveness and compatibility of different medical readability tools via machine learning.

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“…Total syllables per word were taken as factor in Fiesch Reading Ease [30], Douma [41], Das and Roychudhury [30] and Forcast [35]. Das and Roychudhury [30] counts number of monosyllabic words whereas in Fry Graph [21] number of syllables in 100 words sample and in Kane [40] Das and Roychudhury [30] number of different words with 3 or more syllables were taken as readability factor.…”

Section: Syllablesmentioning

confidence: 99%

Theoretical Orientation for Readability Assessment in Bengali Language of Extension Literatures Related to Farming

Saha

Basu

Sarkar

2019

AJAEES

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Readability of a text generally refers to how well a reader can comprehend the content of a text, through reading. Readability is closely related to the understandability of the messages. Extension education is an applied behavioural science. Its main purpose is to bring about desirable changes in human behaviour usually through different strategies and programme of change and by applying the latest scientiﬁc and technological innovations where extension messages are sent largely through text. In Bengali language, only a few works on readability is found but their study is restricted to broad range of documents like newspaper article, short stories, interviews, and blogs to philosophical articles but there is no such research done on readability of Bengali extension literatures targeting the farming community. So, there is a need for studying on readability of Bengali extension literature for promotion of agricultural education. Assessment of readability of Bengali extension literatures is an imperative task for promotion of agriculture education among the millions of farmers who speaks and read in Bengali language across this subcontinent and Bangladesh with a view that the text messages become more understandable to the target audience. In this context the present theoretical orientation had been prepared with the objectives to measure the readability of Extension literatures in Bengali Language related to farming. Apart from that the analytical tools or procedures used in readability assessment of a Bengali text associated with farming extension literature were also summarized.

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Readability of Arabic Medicine Information Leaflets: A Machine Learning Approach

Cited by 8 publications

References 12 publications

ChatGPT's Ability to Assess Quality and Readability of Online Medical Information: Evidence From a Cross-Sectional Study

ChatGPT's Ability to Assess Quality and Readability of Online Medical Information: Evidence From a Cross-Sectional Study

Combining Readability Formulas and Machine Learning for Reader-oriented Evaluation of Online Health Resources

Theoretical Orientation for Readability Assessment in Bengali Language of Extension Literatures Related to Farming

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