Publications by authors named "H P Trivedi"
This study assesses the feasibility of Large Language Models like GPT-4 (OpenAI, San Francisco, CA, USA) to summarize interventional radiology (IR) procedural reports to improve layperson understanding and translate medical texts into multiple languages. 200 reports from eight categories were summarized using GPT-4. Readability was assessed with Flesch-Kincaid Reading Level (FKRL) and Flesch Reading Ease Score (FRES).
View Article and Find Full Text PDFBackground: The increasing prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), parallels the rise in sedentary lifestyles. MASLD is the most common form of steatotic liver disease (SLD), which represents the umbrella beneath which the vast majority of chronic liver diseases fall, including alcohol-related liver disease and their overlap. These conditions are the leading contributors to chronic liver disease, significantly impacting global morbidity and mortality.
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- Second look flexible nephroscopy (SLFN) is performed after percutaneous nephrolithotomy (PCNL) in patients with residual fragments (RFs) to assess and potentially remove any remaining stones.
- In a study involving 201 patients, the final stone-free rate after SLFN was found to be 60.7%, despite many still having RFs post-procedure, with factors like bilateral stones and larger stone burdens linked to persistent fragments.
- The study highlights that even with aggressive removal efforts during both PCNL and SLFN, some patients may still retain stone fragments, though the risk of complications from these fragments is currently unclear.
Wound healing in the oral mucosa is superior to that in the skin, with faster wound closure accompanied by reduced inflammation, less angiogenesis, and minimal scar formation. A well-characterized oral wound model is critical to investigating the mechanisms of oral wound closure and the efficacy of various clinical interventions. Currently, there are a few human oral wound models, although none of them are well characterized.
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- This review analyzes various mammography datasets used for AI development in breast cancer screening, focusing on their transparency, content, and accessibility.
- A search identified 254 datasets, with only 28 being accessible; most datasets came from Europe, East Asia, and North America, raising concerns over poor demographic representation.
- The findings highlight significant gaps in diversity within these datasets, underscoring the need for better documentation and inclusivity to enhance the effectiveness of AI technologies in breast cancer research.