Clinical application potential of large language model: a study based on thyroid nodules.

Background: Limited data indicated the performance of large language model (LLM) taking on the role of doctors. We aimed to investigate the potential for ChatGPT-3.5 and New Bing Chat acting as doctors using thyroid nodules as an example.

Mathematical models and analysis tools for risk assessment of unnatural epidemics: a scoping review.

Predicting, issuing early warnings, and assessing risks associated with unnatural epidemics (UEs) present significant challenges. These tasks also represent key areas of focus within the field of prevention and control research for UEs. A scoping review was conducted using databases such as PubMed, Web of Science, Scopus, and Embase, from inception to 31 December 2023.

Transforming free-text radiology reports into structured reports using ChatGPT: A study on thyroid ultrasonography.

Purpose: The importance of structured radiology reports has been fully recognized, as they facilitate efficient data extraction and promote collaboration among healthcare professionals. Our purpose is to assess the accuracy and reproducibility of ChatGPT, a large language model, in generating structured thyroid ultrasound reports.

Methods: This is a retrospective study that includes 184 nodules in 136 thyroid ultrasound reports from 136 patients.

Risk Prediction for Sudden Cardiac Death in the General Population: A Systematic Review and Meta-Analysis.

Identification of SCD risk is important in the general population from a public health perspective. The objective is to summarize and appraise the available prediction models for the risk of SCD among the general population. Data were obtained searching six electronic databases and reporting prediction models of SCD risk in the general population.

Performance of large language models on benign prostatic hyperplasia frequently asked questions.

Background: Benign prostatic hyperplasia (BPH) is a common condition, yet it is challenging for the average BPH patient to find credible and accurate information about BPH. Our goal is to evaluate and compare the accuracy and reproducibility of large language models (LLMs), including ChatGPT-3.5, ChatGPT-4, and the New Bing Chat in responding to a BPH frequently asked questions (FAQs) questionnaire.

Full Stokes polarimetry based on an inverse-designed multi-foci metalens.

In the realm of metasurface-based polarimetry, well-known for its remarkable compactness and integration capabilities, previous attempts have been hindered by limitations such as the restricted choices of target polarization states and the inefficient focusing of light. To address these problems, this study introduces and harnesses a novel, to our knowledge, forward-solving model, grounded in the equivalence principle and dyadic Green's function, to inversely optimize the vectorial focusing patterns of metalenses. Leveraging this methodology, we develop and experimentally validate a single multi-foci metalens-based polarimeter, capable of simultaneously separating and concentrating four distinct elliptical polarization states at a wavelength of 10.

An efficient framework for lesion segmentation in ultrasound images using global adversarial learning and region-invariant loss.

Lesion segmentation in ultrasound images is an essential yet challenging step for early evaluation and diagnosis of cancers. In recent years, many automatic CNN-based methods have been proposed to assist this task. However, most modern approaches often lack capturing long-range dependencies and prior information making it difficult to identify the lesions with unfixed shapes, sizes, locations, and textures.

Enhanced Biogenic Sulfidation of Zero-Valent Iron in Columns: Implications for Promoting Dechlorination in Permeable Reactive Barriers.

Biogenic sulfidation of zero-valent iron (ZVI) using sulfate reducing bacteria (SRB) has shown enhanced dechlorination rates comparable to those produced by chemical sulfidation. However, controlling and sustaining biogenic sulfidation to enhance in situ dechlorination are poorly understood. Detailed interactions between SRB and ZVI were examined for 4 months in column experiments under enhanced biogenic sulfidation conditions.

Generalizability and Diagnostic Performance of AI Models for Thyroid US.

Background Artificial intelligence (AI) models have improved US assessment of thyroid nodules; however, the lack of generalizability limits the application of these models. Purpose To develop AI models for segmentation and classification of thyroid nodules in US using diverse data sets from nationwide hospitals and multiple vendors, and to measure the impact of the AI models on diagnostic performance. Materials and Methods This retrospective study included consecutive patients with pathologically confirmed thyroid nodules who underwent US using equipment from 12 vendors at 208 hospitals across China from November 2017 to January 2019.

AMES: An Automated Self-Administered Scale to Detect Incipient Cognitive Decline in Primary Care Settings.

Early identification and intervention of cognitive decline could be effective to prevent progression to dementia. We developed a self-delivered cognitive screening tool, Automated Memory and Executive Screening (AMES), to assess cognitive domains including memory, language, and executive function. 189 participants with diagnoses of mild cognitive impairment (MCI, = 43), subjective cognitive decline (SCD, = 29), objectively-defined subtle cognitive decline (obj-SCD, = 18), and normal controls (NC, = 99) completed the study.

Multi-Attribute Attention Network for Interpretable Diagnosis of Thyroid Nodules in Ultrasound Images.

Ultrasound (US) is the primary imaging technique for the diagnosis of thyroid cancer. However, accurate identification of nodule malignancy is a challenging task that can elude less-experienced clinicians. Recently, many computer-aided diagnosis (CAD) systems have been proposed to assist this process.

The uptake of metal-organic frameworks: a journey into the cell.

The application of metal-organic frameworks (MOFs) in drug delivery has advanced rapidly over the past decade, showing huge progress in the development of novel systems. Although a large number of versatile MOFs that can carry and release multiple compounds have been designed and tested, one of the main limitations to their translation to the clinic is the limited biological understanding of their interaction with cells and the way they penetrate them. This is a crucial aspect of drug delivery, as MOFs need to be able not only to enter into cells but also to release their cargo in the correct intracellular location.

Boundary-rendering network for breast lesion segmentation in ultrasound images.

Breast Ultrasound (BUS) has proven to be an effective tool for the early detection of cancer in the breast. A lesion segmentation provides identification of the boundary, shape, and location of the target, and serves as a crucial step toward accurate diagnosis. Despite recent efforts in developing machine learning algorithms to automate this process, problems remain due to the blurry or occluded edges and highly irregular nodule shapes.

Oxygen-Independent Sulfate Radical for Stimuli-Responsive Tumor Nanotherapy.

Variant modalities are quested and merged into the tumor nanotherapy by leveraging the excitation from external or intratumoral incentives. However, the ubiquitous hypoxia and the insufficient content of hydrogen peroxide (H O ) in tumor microenvironments inevitably hinder the effective production of reactive oxygen species (ROS). To radically extricate from the shackles, peroxymonosulfate (PMS: HSO )-loaded hollow mesoporous copper sulfide (CuS) nanoparticles (NPs) are prepared as the distinct ROS donors for sulfate radical (•SO )-mediated and stimuli-responsive tumor nanotherapy in an oxygen-independent manner.

AW3M: An auto-weighting and recovery framework for breast cancer diagnosis using multi-modal ultrasound.

Recently, more clinicians have realized the diagnostic value of multi-modal ultrasound in breast cancer identification and began to incorporate Doppler imaging and Elastography in the routine examination. However, accurately recognizing patterns of malignancy in different types of sonography requires expertise. Furthermore, an accurate and robust diagnosis requires proper weights of multi-modal information as well as the ability to process missing data in practice.

Chlorogenic acid inhibits forming of diabetes mellitus in rats induced by high-fat high-sucrose and streptozotocin.

To evaluate the inhibitory effect of chlorogenic acid on the forming of type 2 diabetes mellitus (T2DM), using Sprague Dawley (SD) rats, a recognized T2DM model induced by high-fat high-sucrose diet (HFSD) and streptozotocin (STZ). Thirty female SD rats were assigned equally to three groups randomly: normal control with standard commercial (NC), chlorogenic acid treatment with HFSD and chlorogenic acid (90mg/kg, CA), and diabetes model with HFSD (DM). Upon treatment with chlorogenic acid, suppression of the onset of diabetes, reduced serum glucose and insulin concentrations, improved glucose tolerance and increased body weight and visceral fat weight were observed.

Analytical method development and comparability study for AmBisome® and generic Amphotericin B liposomal products.

Liposomal Amphotericin B, known as AmBisome®, is a life-saving antifungal product that sold $407 million in 2019. AmBisome® has a rather complex physical structure in that Amphotericin B (AmpB) forms a stable ionic complex with the lipid bilayer to maintain AmBisome®'s low toxicity and high stability in systemic circulation. Failed attempts to reproduce AmBisome®'s precise structure has resulted in faster drug release and higher toxicity both in vitro and in vivo.

Activatable NIR-II photoacoustic imaging and photochemical synergistic therapy of MRSA infections using miniature Au/Ag nanorods.

Multidrug-resistant Staphylococcus aureus (MRSA) seriously endanger human health. The development of efficient methods to eliminate the infections and monitor the treatment process are of great significance. Near-infrared-II (NIR-II) photoacoustic (PA) imaging and photothermal therapy (PTT) are highly integrated theranostic platforms with superior performance including a low imaging background, increased tissue penetration depth, and high photothermal threshold.

Abdominal adipose tissue thickness measured using magnetic resonance imaging is associated with lumbar disc degeneration in a Chinese patient population.

The relationship between abdominal adiposity and disc degeneration remains largely uninvestigated. Here, we investigated the association between abdominal adipose tissue thickness and lumbar disc degeneration in a cross-sectional study of 2415 participants from The Second Affiliated Hospital of Wenzhou Medical University. All subjects were scanned with a 3T Magnetic Resonance Imaging system to evaluate the degree of lumbar disc degeneration.