e.g. mhealth
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Effective physician-patient communication is essential in clinical practice, particularly in oncology, where radiology reports play a crucial role. These reports, often filled with technical jargon, can be challenging for patients to understand, impacting their engagement and decision-making.
Large language models (LLMs), such as GPT-4, offer a novel approach to simplifying these reports, potentially enhancing communication and improving patient outcomes.
J Med Internet Res 2025;27:e63786
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In this context, their oncology departments together with the 6 university hospitals` DIC have established a federated observational research network, building on the groundwork laid by the MII. Analyzing data from multiple hospitals enhances statistical validity by increasing the sample size, which enables rare event analysis in more diverse patient populations.
J Med Internet Res 2025;27:e65681
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Recognizing the complexity that patients face, the consortium seeks to use design methods (particularly the Metro Mapping methodology, Figure 1) to improve care paths in oncology. This involves the development of innovative prognostic models and conversation tools that consider patient experiences, values, and preferences through models partly based on artificial intelligence (AI).
JMIR Cancer 2025;11:e65566
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Breast Cancer Vlogs on YouTube: Descriptive and Content Analyses
oncology
JMIR Infodemiology 2025;5:e66812
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Large Language Model Applications for Health Information Extraction in Oncology: Scoping Review
Our scoping review of 24 studies highlights significant research interest in designing, evaluating, and deploying LLMs for data extraction from clinical text in oncology. The most commonly used LLMs for data extraction from clinical text in oncology include BERT and Chat-GPT, two of the most well-known LLMs in NLP research.
JMIR Cancer 2025;11:e65984
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Despite the postulated importance of NNs in DRM, more research is needed to explore the extent to which they contribute to the effectiveness of these systems, especially in oncology. This study aims to fill this gap by examining the impact of NNs in the Cancérologie parcours région Ile-de-France (CAPRI) DRM program, considering factors such as toxicity management and care use.
CAPRI is an application of DRM in oncology.
J Med Internet Res 2025;27:e66275
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The American Society of Clinical Oncology and the Oncology Nursing Society jointly released evidence-based guidelines and OAA management standards. These emphasize patient education at OAA initiation and ongoing monitoring throughout treatment to enable early identification of side effects and toxicities, thus preventing complications [27,28]. Consequently, there is a need for more timely and more accessible patient support for individuals taking OAAs [28].
JMIR Res Protoc 2025;14:e55475
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Reference 4: Chatbot for health care and oncology applications using artificial intelligence and machineoncology
JMIR Dermatol 2025;8:e67551
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Stakeholders consisted of thyroid surgeons (n=1), endocrinologists (n=2), nuclear medicine specialists (n=1), palliative care providers (n=2), patient advocates (n=2), psycho-oncologists (n=1), registered oncology dietitians (n=2), and social workers (n=1). Table 1 presents sample characteristics of focus group participants and stakeholders and Table 2 presents clinical characteristics of focus group participants.
JMIR Form Res 2025;9:e60588
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Health literacy is particularly important in oncology, where the advancement in cancer treatment beyond traditional methods has positioned patients and their families even more in the center of making care decisions [8]. Upon receiving a cancer diagnosis, patients often turn to various sources for more information, such as the internet, forums, social support groups, and literature [9,10].
JMIR Cancer 2025;11:e63347
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