An Effective Methodology for Diabetes Prediction in the Case of Class Imbalance DOI Creative Commons
Borislava Toleva,

I. Atanasov,

Ivan Ivanov

et al.

Bioengineering, Journal Year: 2025, Volume and Issue: 12(1), P. 35 - 35

Published: Jan. 6, 2025

Diabetes causes an increase in the level of blood sugar, which leads to damage various parts human body. data are used not only for providing a deeper understanding treatment mechanisms but also predicting probability that one might become sick. This paper proposes novel methodology perform classification case heavy class imbalance, as observed PIMA diabetes dataset. The proposed uses two steps, namely resampling and random shuffling prior defining model. is tested with versions cross validation appropriate cases imbalance-k-fold stratified k-fold validation. Our findings suggest when having imbalanced data, randomly train/test split can help improve estimation metrics. outperform existing machine learning algorithms complex deep models. Applying our simple fast way predict labels imbalance. It does require additional techniques balance classes. involve preselecting important variables, saves time makes model easy analysis. it effective initial further modeling Moreover, methodologies show how effectiveness models based on standard approaches make them more reliable.

Language: Английский

Patient- and clinician-based evaluation of large language models for patient education in prostate cancer radiotherapy DOI Creative Commons
Christian Trapp,

Nina Schmidt-Hegemann,

Michael Keilholz

et al.

Strahlentherapie und Onkologie, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 10, 2025

Abstract Background This study aims to evaluate the capabilities and limitations of large language models (LLMs) for providing patient education men undergoing radiotherapy localized prostate cancer, incorporating assessments from both clinicians patients. Methods Six questions about definitive cancer were designed based on common inquiries. These presented different LLMs [ChatGPT‑4, ChatGPT-4o (both OpenAI Inc., San Francisco, CA, USA), Gemini (Google LLC, Mountain View, Copilot (Microsoft Corp., Redmond, WA, Claude (Anthropic PBC, USA)] via respective web interfaces. Responses evaluated readability using Flesch Reading Ease Index. Five radiation oncologists assessed responses relevance, correctness, completeness a five-point Likert scale. Additionally, 35 patients ChatGPT‑4 comprehensibility, accuracy, trustworthiness, overall informativeness. Results The Index indicated that all relatively difficult understand. All provided answers found be generally relevant correct. ChatGPT‑4, ChatGPT-4o, AI also complete. However, we significant differences between performance regarding relevance completeness. Some lacked detail or contained inaccuracies. Patients perceived information as easy understand relevant, with most expressing confidence in willingness use future medical questions. ChatGPT-4’s helped feel better informed, despite initially standardized provided. Conclusion Overall, show promise tool radiotherapy. While improvements are needed terms accuracy readability, positive feedback suggests can enhance understanding engagement. Further research is essential fully realize potential artificial intelligence education.

Language: Английский

Citations

0
Evaluating an Artificially Intelligent Chatbot ‘Prostate Cancer Info’ for Providing Quality Prostate Cancer Screening Information: A Cross-Sectional Study (Preprint) DOI Creative Commons
Otis L. Owens,

Michael Leonard

Published: Feb. 16, 2025

BACKGROUND Generative AI Chatbots may be useful tools for supporting shared prostate cancer screening decisions, but the information produced by these sometimes lack quality or credibility. ‘Prostate Cancer Info’ is a custom GPT chatbot developed to provide plain-language PrCA only from websites of key authorities on and peer-reviewed literature. OBJECTIVE To evaluate accuracy, completeness, readability Info’s responses frequently asked questions. METHODS Twenty-three questions were individually input into Info.’ Responses recorded in Microsoft Word reviewed two raters their accuracy completeness. Readability content was determined pasting an online Flesch Kincaid Reading Ease Scores calculator. RESULTS all accurate culturally appropriate. Seventeen twenty-three (74%) had complete responses. The average 64.5 (written at 8th-grade level). CONCLUSIONS chatbots, such as Prostate Info, are great starting places learning about preparing engage decision making should not used independent sources because omitted. Men encouraged use complement received form healthcare provider.

Language: Английский

Citations

0
Performance of artificial intelligence chatbots in responding to the frequently asked questions of patients regarding dental prostheses DOI Creative Commons

Hossein Esmailpour,

Vanya Rasaie, Yasamin Babaee Hemmati

et al.

BMC Oral Health, Journal Year: 2025, Volume and Issue: 25(1)

Published: April 15, 2025

Artificial intelligence (AI) chatbots are increasingly used in healthcare to address patient questions by providing personalized responses. Evaluating their performance is essential ensure reliability. This study aimed assess the of three AI responding frequently asked (FAQs) patients regarding dental prostheses. Thirty-one were collected from accredited organizations' websites and "People Also Ask" feature Google, focusing on removable fixed prosthodontics. Two board-certified prosthodontists evaluated response quality using modified Global Quality Score (GQS) a 5-point Likert scale. Inter-examiner agreement was assessed weighted kappa. Readability measured Flesch-Kincaid Grade Level (FKGL) Flesch Reading Ease (FRE) indices. Statistical analyses performed repeated measures ANOVA Friedman test, with Bonferroni correction for pairwise comparisons (α = 0.05). The inter-examiner good. Among chatbots, Google Gemini had highest score (4.58 ± 0.50), significantly outperforming Microsoft Copilot (3.87 0.89) (P =.004). analysis showed ChatGPT (10.45 1.26) produced more complex responses compared (7.82 1.19) (8.38 1.59) <.001). FRE scores indicated that ChatGPT's categorized as fairly difficult (53.05 7.16), while Gemini's plain English (64.94 7.29), significant difference between them show great potential answering inquiries about However, improvements needed enhance effectiveness education tools.

Language: Английский

Citations

0
Evaluating an Artificially Intelligent Chatbot ‘Prostate Cancer Info’ for Providing Quality Prostate Cancer Screening Information: A Cross-Sectional Study (Preprint) DOI Creative Commons
Otis L. Owens,

Michael Leonard

JMIR Cancer, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 16, 2025

Language: Английский

Citations

0
An Effective Methodology for Diabetes Prediction in the Case of Class Imbalance DOI Creative Commons
Borislava Toleva,

I. Atanasov,

Ivan Ivanov

et al.

Bioengineering, Journal Year: 2025, Volume and Issue: 12(1), P. 35 - 35

Published: Jan. 6, 2025

Diabetes causes an increase in the level of blood sugar, which leads to damage various parts human body. data are used not only for providing a deeper understanding treatment mechanisms but also predicting probability that one might become sick. This paper proposes novel methodology perform classification case heavy class imbalance, as observed PIMA diabetes dataset. The proposed uses two steps, namely resampling and random shuffling prior defining model. is tested with versions cross validation appropriate cases imbalance-k-fold stratified k-fold validation. Our findings suggest when having imbalanced data, randomly train/test split can help improve estimation metrics. outperform existing machine learning algorithms complex deep models. Applying our simple fast way predict labels imbalance. It does require additional techniques balance classes. involve preselecting important variables, saves time makes model easy analysis. it effective initial further modeling Moreover, methodologies show how effectiveness models based on standard approaches make them more reliable.

Language: Английский

Citations

0