JMIR Cancer, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 8, 2024
Language: Английский
Systems, Journal Year: 2025, Volume and Issue: 13(4), P. 281 - 281
Published: April 10, 2025
The integration of large language models (LLMs) into remote healthcare has the potential to revolutionize medication management by enhancing communication, improving adherence, and supporting clinical decision-making. This study aims explore role LLMs in management, focusing on their impact. paper comprehensively reviews existing literature, medical LLM cases, commercial applications healthcare. It also addresses technical, ethical, regulatory challenges related use artificial intelligence (AI) this context. review methodology includes analyzing studies applications, comparing impact, identifying gaps for future research development. reveals that have shown significant communication between patients providers, adherence monitoring, decision-making management. Compared traditional reminder systems, AI systems a 14% higher rate rates pilot studies. However, there are notable challenges, including data privacy concerns, system issues, ethical dilemmas AI-driven decisions such as bias transparency. Overall, offers comprehensive analysis both transformative key be addressed. provides insights policymakers, researchers optimizing
Language: Английский
Citations
0
JMIR Cancer, Journal Year: 2025, Volume and Issue: 11, P. e63677 - e63677
Published: April 16, 2025
Abstract Background Patients frequently resort to the internet access information about cancer. However, these websites often lack content accuracy and readability. Recently, ChatGPT, an artificial intelligence–powered chatbot, has signified a potential paradigm shift in how patients with cancer can vast amounts of medical information, including insights into radiotherapy. quality provided by ChatGPT remains unclear. This is particularly significant given general public’s limited knowledge this treatment concerns its possible side effects. Furthermore, evaluating responses crucial, as misinformation foster false sense security, lead noncompliance, result delays receiving appropriate treatment. Objective study aims evaluate reliability ChatGPT’s common patient queries radiotherapy, comparing performance two versions: GPT-3.5 GPT-4. Methods We selected 40 commonly asked radiotherapy questions entered both versions ChatGPT. Response were evaluated 16 experts using General Quality Score (GQS), 5-point Likert scale, median GQS determined based on experts’ ratings. Consistency similarity assessed cosine score, which ranges from 0 (complete dissimilarity) 1 similarity). Readability was analyzed Flesch Reading Ease Score, ranging 100, Flesch-Kincaid Grade Level, reflecting average number years education required for comprehension. Statistical analyses performed Mann-Whitney test effect size, results deemed at 5% level ( P =.05). To assess agreement between experts, Krippendorff α Fleiss κ used. Results GPT-4 demonstrated superior performance, higher lower scores 2, compared GPT-3.5. The revealed statistically differences some questions, generally (IQR) score indicated substantial (0.81, IQR 0.05) consistency (GPT-3.5: 0.85, 0.04; GPT-4: 0.83, 0.04). considered college level, scoring slightly better (34.61) Level (12.32) (32.98 13.32, respectively). Responses challenging public. Conclusions Both having capability address concepts, showing performance. models present readability challenges population. Although demonstrates valuable resource addressing related it imperative acknowledge limitations, risks issues. In addition, implementation should be supported strategies enhance accessibility
Language: Английский
Citations
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Journal of Medical Internet Research, Journal Year: 2025, Volume and Issue: unknown
Published: Feb. 13, 2025
Language: Английский
Citations
0
The Oncologist, Journal Year: 2025, Volume and Issue: 30(4)
Published: March 29, 2025
Abstract Background Recent advances in large language models (LLM) have enabled human-like qualities of natural competency. Applied to oncology, LLMs been proposed serve as an information resource and interpret vast amounts data a clinical decision-support tool improve outcomes. Objective This review aims describe the current status medical accuracy oncology-related LLM applications research trends for further areas investigation. Methods A scoping literature search was conducted on Ovid Medline peer-reviewed studies published since 2000. We included primary that evaluated model applied oncology settings. Study characteristics outcomes were extracted landscape LLMs. Results Sixty based inclusion exclusion criteria. The majority health question-answer style examinations (48%), followed by diagnosis (20%) management (17%). number utility fine-tuning prompt-engineering increased over time from 2022 2024. Studies reported advantages accurate resource, reduction clinician workload, improved accessibility readability information, while noting disadvantages such poor reliability, hallucinations, need oversight. Discussion There exists significant interest application with particular focus decision support tool. However, is needed validate these tools external hold-out datasets generalizability across diverse scenarios, underscoring supervision tools.
Language: Английский
Citations
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Practical Radiation Oncology, Journal Year: 2025, Volume and Issue: unknown
Published: April 1, 2025
Language: Английский
Citations
0
EBioMedicine, Journal Year: 2025, Volume and Issue: 115, P. 105695 - 105695
Published: April 29, 2025
Language: Английский
Citations
0
Machine Learning and Knowledge Extraction, Journal Year: 2024, Volume and Issue: 6(2), P. 1145 - 1153
Published: May 24, 2024
Introduction: Large language models (LLMs), such as ChatGPT, are a topic of major public interest, and their potential benefits threats subject discussion. The contribution these to health care is widely discussed. However, few studies date have examined LLMs. For example, the use LLMs in (individualized) informed consent remains unclear. Methods: We analyzed performance ChatGPT 3.5, 4.0, Gemini with regard ability create an information sheet for six basic anesthesiologic procedures response corresponding questions. performed multiple attempts forms anesthesia results checklists based on existing standard sheets. Results: None tested were able legally compliant any procedure. Overall, fewer than one-third risks, procedural descriptions, preparations listed covered by Conclusions: There clear limitations current terms practical application. Advantages generation patient-adapted risk stratification within individual not available at moment, although further development difficult predict.
Language: Английский
Citations
3
Cancers, Journal Year: 2024, Volume and Issue: 16(13), P. 2311 - 2311
Published: June 24, 2024
This study aimed to develop a retrained large language model (LLM) tailored the needs of HN cancer patients treated with radiotherapy, emphasis on symptom management and survivorship care.
Language: Английский
Citations
1
iScience, Journal Year: 2024, Volume and Issue: 27(12), P. 111493 - 111493
Published: Nov. 29, 2024
Language: Английский
Citations
1
Current Problems in Diagnostic Radiology, Journal Year: 2024, Volume and Issue: unknown
Published: Dec. 1, 2024
Language: Английский
Citations
1