Publications by authors named "D Steybe"

The potential of large language models (LLMs) in medical applications is significant, and Retrieval-augmented generation (RAG) can address the weaknesses of these models in terms of data transparency and scientific accuracy by incorporating current scientific knowledge into responses. In this study, RAG and GPT-4 by OpenAI were applied to develop GuideGPT, a context aware chatbot integrated with a knowledge database from 449 scientific publications designed to provide answers on the prevention, diagnosis, and treatment of medication-related osteonecrosis of the jaw (MRONJ). A comparison was made with a generic LLM ("PureGPT") across 30 MRONJ-related questions.

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Article Synopsis
  • Patients treated with both antiresorptive medication and radiotherapy in the head and neck are at increased risk for developing complications such as jaw necrosis, fractures, and recurrence of conditions.
  • The study involved 17 patients who were compared to larger control groups, revealing significant differences in outcomes, with those receiving combined treatment facing higher risks.
  • The findings suggest that the combination of these treatments leads to a four-fold increase in recurrence risk and a higher likelihood of serious complications compared to patients receiving just one type of treatment.
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Computer technology-based treatment approaches like intraoperative navigation and intensity-modulated radiation therapy have become important components of state of the art head and neck cancer treatment. Multidirectional exchange of virtual three-dimensional patient data via an interdisciplinary platform allows all medical specialists involved in the patients treatment to take full advantage of these technologies. This review article gives an overview of current technologies and future directions regarding treatment approaches that are based on a virtual, three-dimensional patient specific dataset: storage and exchange of spatial information acquired via intraoperative navigation allow for a highly precise frozen section procedure.

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Stimulated Raman Histology (SRH) employs the stimulated Raman scattering (SRS) of photons at biomolecules in tissue samples to generate histological images. Subsequent pathological analysis allows for an intraoperative evaluation without the need for sectioning and staining. The objective of this study was to investigate a deep learning-based classification of oral squamous cell carcinoma (OSCC) and the sub-classification of non-malignant tissue types, as well as to compare the performances of the classifier between SRS and SRH images.

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X-linked hypophosphatemia is a rare, hereditary disorder that significant influences teeth and alveolar bone. The first clinical sign leading to the diagnosis of X-linked hypophosphatemia is often dental impairment with dental abscesses and dentin mineralization defects. Genetic analysis helped find the responsible gene and therefore opened up new ways of therapeutically managing X-linked hypophosphatemia.

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