Conectar
To compare the quality and time efficiency of physician-written summaries with customised large language model (LLM)-generated medical summaries integrated into the electronic health record (EHR) in a non-English clinical environment.
Cross-sectional non-inferiority validation study.
Tertiary academic hospital.
52 physicians from 8 specialties at a large Dutch academic hospital participated, either in writing summaries (n=42) or evaluating them (n=10).
Physician writers wrote summaries of 50 patient records. LLM-generated summaries were created for the same records using an EHR-integrated LLM. An independent, blinded panel of physician evaluators compared physician-written summaries to LLM-generated summaries.
Primary outcome measures were completeness, correctness and conciseness (on a 5-point Likert scale). Secondary outcomes were preference and trust, and time to generate either the physician-written or LLM-generated summary.
The completeness and correctness of LLM-generated summaries did not differ significantly from physician-written summaries. However, LLM summaries were less concise (3.0 vs 3.5, p=0.001). Overall evaluation scores were similar (3.4 vs 3.3, p=0.373), with 57% of evaluators preferring LLM-generated summaries. Trust in both summary types was comparable, and interobserver variability showed excellent reliability (intraclass correlation coefficient 0.975). Physicians took an average of 7 min per summary, while LLMs completed the same task in just 15.7 s.
LLM-generated summaries are comparable to physician-written summaries in completeness and correctness, although slightly less concise. With a clear time-saving benefit, LLMs could help reduce clinicians’ administrative burden without compromising summary quality.
by Vahid Sadeghi, Alireza Mehridehnavi, Maryam Behdad, Alireza Vard, Mina Omrani, Mohsen Sharifi, Yasaman Sanahmadi, Niloufar Teyfouri
A considerable amount of undesirable factors in the wireless capsule endoscopy (WCE) procedure hinder the proper visualization of the small bowel and take gastroenterologists more time to review. Objective quantitative assessment of different bowel preparation paradigms and saving the physician reviewing time motivated us to present an automatic low-cost statistical model for automatically segmenting of clean and contaminated regions in the WCE images. In the model construction phase, only 20 manually pixel-labeled images have been used from the normal and reduced mucosal view classes of the Kvasir capsule endoscopy dataset. In addition to calculating prior probability, two different probabilistic tri-variate Gaussian distribution models (GDMs) with unique mean vectors and covariance matrices have been fitted to the concatenated RGB color pixel intensity values of clean and contaminated regions separately. Applying the Bayes rule, the membership probability of every pixel of the input test image to each of the two classes is evaluated. The robustness has been evaluated using 5 trials; in each round, from the total number of 2000 randomly selected images, 20 and 1980 images have been used for model construction and evaluation modes, respectively. Our experimental results indicate that accuracy, precision, specificity, sensitivity, area under the receiver operating characteristic curve (AUROC), dice similarity coefficient (DSC), and intersection over union (IOU) are 0.89 ± 0.07, 0.91 ± 0.07, 0.73 ± 0.20, 0.90 ± 0.12, 0.92 ± 0.06, 0.92 ± 0.05 and 0.86 ± 0.09, respectively. The presented scheme is easy to deploy for objectively assessing small bowel cleansing score, comparing different bowel preparation paradigms, and decreasing the inspection time. The results from the SEE-AI project dataset and CECleanliness database proved that the proposed scheme has good adaptability.by Zeinab Pourhashem, Leila Nourani, Sakineh Pirahmadi, Hemn Yousefi, Jafar J. Sani, Abbasali Raz, Sedigheh Zakeri, Navid Dinparast Djadid, Akram Abouie Mehrizi
BackgroundsMalaria, a preventive and treatable disease, is still responsible for annual deaths reported in most tropical regions, principally in sub-Saharan Africa. Subunit recombinant transmission-blocking vaccines (TBVs) have been proposed as promising vaccines to succeed in malaria elimination and eradication. Here, a provisional study was designed to assess the immunogenicity and functional activity of alanyl aminopeptidase N (APN1) of Anopheles stephensi, as a TBV candidate, administered with MPL, CpG, and QS21 adjuvants in the murine model.
Methodology/Principal findingsThe mouse groups were immunized with recombinant APN1 (rAPN1) alone or formulated with CpG, MPL, QS-21, or a combination of adjuvants (CMQ), and the elicited immune responses were evaluated after the third immunization. The standard membrane feeding assay (SMFA) measured the functional activity of antibodies against bacterial-expressed APN1 protein in adjuvanted vaccine groups on transmission of P. falciparum (NF54) to An. stephensi mosquitoes. Evaluation of mice vaccinated with rAPN1 formulated with distinct adjuvants manifested a significant increase in the high-avidity level of anti-APN1 IgG and IgG subclasses; however, rAPN1 induced the highest level of high-avidity anti-APN1 IgG1, IgG2a, and IgG2b antibodies in the immunized vaccine group 5 (APN1/CMQ). In addition, vaccine group 5 (receiving APN1/CMQ), had still the highest level of anti-APN1 IgG antibodies relative to other immunized groups after six months, on day 180. The SMFA data indicates a trend towards higher transmission-reducing activity in groups 2 and 5, which received the antigen formulated with CpG or a combination of three adjuvants.
Conclusions/SignificanceThe results have shown the capability of admixture to stimulate high-affinity and long-lasting antibodies against the target antigen to hinder Plasmodium parasite development in the mid-gut of An. stephensi. The attained results authenticated APN1/CMQ and APN1/CpG as a potent APN1-based TBV formulation which will be helpful in designing a vaccine in the future.
Wound healing is a complex process that orchestrates the coordinated action of various cells, cytokines and growth factors. Nanotechnology offers exciting new possibilities for enhancing the healing process by providing novel materials and approaches to deliver bioactive molecules to the wound site. This article elucidates recent advancements in utilizing nanoparticles, nanofibres and nanosheets for wound healing. It comprehensively discusses the advantages and limitations of each of these materials, as well as their potential applications in various types of wounds. Each of these materials, despite sharing common properties, can exhibit distinct practical characteristics that render them particularly valuable for healing various types of wounds. In this review, our primary focus is to provide a comprehensive overview of the current state-of-the-art in applying nanoparticles, nanofibres, nanosheets and their combinations to wound healing, serving as a valuable resource to guide researchers in their appropriate utilization of these nanomaterials in wound-healing research. Further studies are necessary to gain insight into the application of this type of nanomaterials in clinical settings.
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