Evaluation of a context-aware chatbot using retrieval-augmented generation for answering clinical questions on medication-related osteonecrosis of the jaw.

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.

Pomegranate juice ameliorates craving and oxidative stress on patients under medication for opioid addiction treatment with methadone and buprenorphine: a Ranzomised Controlled Trial.

Background & Aims: Buprenorphine and methadone are drugs used as medication for addiction treatment for patients with opioid use disorders (OUDs). However, scarce evidence indicates that they induce oxidative stress, which contributes to the deterioration of psychosocial parameters, thus complicating successful rehab. Therefore, a dietary antioxidant intervention such as pomegranate could be beneficial for that group of patients.

Clinical Outcomes With Immune Checkpoint Inhibitors in Patients With FGFR2/3, MTAP or ERBB2 Genomic Alterations in Advanced Urothelial Carcinoma.

Background: FGFR2/3, MTAP and ERBB2 genomic alterations have treatment targets in advanced urothelial carcinoma (aUC). These alterations may affect tumor microenvironment and outcomes with immune checkpoint inhibitors (ICIs) in aUC.

Patients And Methods: We identified patients with available genomic data in our multi-institution cohort of patients with aUC treated with ICI.

Monitoring of indoor air quality at a large sailing cruise ship to assess ventilation performance and disease transmission risk.

Large passenger ships are characterised as enclosed and crowded indoor spaces with frequent interactions between travellers, providing conditions that facilitate disease transmission. This study aims to provide an indoor ship CO dataset for inferring thermal comfort, ventilation and infectious disease transmission risk evaluation. Indoor air quality (IAQ) monitoring was conducted in nine environments (three cabins, buffet, gym, bar, restaurant, pub and theatre), on board a cruise ship voyaging across the UK and EU, with the study conducted in the framework of the EU HEALTHY SAILING project.

Projections of Public Spending on Pharmaceuticals: A Review of Methods.

Background: Forecasting future public pharmaceutical expenditure is a challenge for healthcare payers, particularly owing to the unpredictability of new market introductions and their economic impact. No best-practice forecasting methods have been established so far. The literature distinguishes between the top-down approach, based on historical trends, and the bottom-up approach, using a combination of historical and horizon scanning data.

The Role of Aspect During Deverbal Word Processing in Greek.

Deverbal formations in Greek, e.g. mi'razo 'to distribute' < 'mirazma 'distributing' are considered morphologically complex lexical items.

Transcatheter Left Ventricular Reconstruction in Heart Failure Patients With Prior Anterior Myocardial Infarction: The Prospective ALIVE Trial.

Background: Left ventricular (LV) dilatation and extensive scar portend a poor prognosis in heart failure (HF). The Revivent TC system (BioVentrix Inc) is used either during a hybrid transcatheter-surgical or a surgical-only procedure to exclude transmural scar and reduce LV dimensions.

Objectives: The purpose of this study was to examine the safety and efficacy of the Revivent TC® anchor system in patients with HF.

First episode of psychosis in rural Greece: A multi-center study of the Mobile Mental Health Units.

Background: Over the last decades the study of schizophrenia-spectrum disorders has been focused on early and comprehensive intervention during the first episode of psychosis (FEP), but studies in rural settings are only rare. In Greece mental healthcare in rural areas is mostly delivered by the locally-based Mobile Mental Health Units (MMHUs).

Aims: The aim of the present study was to address treatment of FEP patients by the MMHUs in rural areas in Greece, focusing on patients with a first episode of schizophrenia.

Current and emerging bone resorption inhibitors for the treatment of osteoporosis.

Introduction: Osteoporosis is a metabolic skeletal disease characterized by low bone mass and strength, and increased risk for fragility fractures. It is a major health issue in aging populations, due to fracture associated increased disability and mortality. Antiresorptive treatments are first line choices in most of the cases.

Biomarkers of Importance in Monitoring Heart Condition After Acute Myocardial Infarction.

Despite notable advancements in cardiovascular medicine, morbidity and mortality rates associated with myocardial infarction (MI) remain high. The unfavourable prognosis and absence of robust post-MI protocols necessitate further intervention. In this comprehensive review, we will focus on well-established and novel biomarkers that can provide insight into the processes that occur after an ischemic event.

Kenny-Caffey Syndrome Type 2 (KCS2): A New Case Report and Patient Follow-Up Optimization.

Kenny-Caffey syndrome 2 (KCS2) is a rare cause of hypoparathyroidism, inherited in an autosomal dominant mode, resulting from pathogenic variants of the gene, which is implicated in intracellular pathways regulating parathormone (PTH) synthesis and skeletal and parathyroid gland development. : The case of a boy is reported, presenting with the characteristic and newly identified clinical, biochemical, radiological, and genetic abnormalities of KCS2. : The proband had noticeable dysmorphic features, and the closure of the anterior fontanel was delayed until the age of 4 years.

Endothelial Glycocalyx Damage and Arterial Thickness in Patients with Retinal Vein Occlusion (RVO).

: Retinal vein occlusion (RVO) is a relatively uncommon condition with a complex pathophysiology. However, its association with traditional cardiovascular risk factors is well established. In this study, we compared arterial stiffness and endothelial function between patients with RVO and healthy controls.

Tidal Volume Challenge to Assess Volume Responsiveness with Dynamic Preload Indices During Non-Cardiac Surgery: A Prospective Study.

: The aim of this study is to assess whether changes in Pulse Pressure Variation (PPV) and Stroke Volume Variation (SVV) following a VtC can predict the response to fluid administration in patients undergoing surgery under general anesthesia with protective mechanical ventilation. : A total of 40 patients undergoing general surgery or vascular surgery without clamping the aorta were enrolled. Protective mechanical ventilation was applied, and the radial artery was catheterized in all patients.

Geotechnical Assessment of Foundation Stability for Preserving the Agrippa Monument at the Acropolis of Athens.

This study focuses on the geotechnical evaluation of the foundation conditions of the Agrippa Monument at the Acropolis of Athens, aiming to propose interventions to improve stability and reduce associated risks. The assessment reveals highly uneven foundation conditions beneath the monument. A thorough collection of bibliographic references and geotechnical surveys was conducted, classifying geomaterials into engineering-geological units and evaluating critical parameters for geotechnical design.

A Comprehensive Survey of Machine Learning Techniques and Models for Object Detection.

Object detection is a pivotal research domain within computer vision, with applications spanning from autonomous vehicles to medical diagnostics. This comprehensive survey presents an in-depth analysis of the evolution and significant advancements in object detection, emphasizing the critical role of machine learning (ML) and deep learning (DL) techniques. We explore a wide spectrum of methodologies, ranging from traditional approaches to the latest DL models, thoroughly evaluating their performance, strengths, and limitations.

EEG in Education: A Scoping Review of Hardware, Software, and Methodological Aspects.

Education is an activity that involves great cognitive load for learning, understanding, concentrating, and other high-level cognitive tasks. The use of the electroencephalogram (EEG) and other brain imaging techniques in education has opened the scientific field of neuroeducation. Insights about the brain mechanisms involved in learning and assistance in the evaluation and optimization of education methodologies according to student brain responses is the main target of this field.

Damage Detection and Identification on Elevator Systems Using Deep Learning Algorithms and Multibody Dynamics Models.

Timely damage detection on a mechanical system can prevent the appearance of catastrophic damage in it, as well as allow for better scheduling of its maintenance and repair process. For this purpose, multiple signal analysis methods have been developed to help identify anomalies in a system, through quantities such as vibrations or deformations in its critical components. In most applications, however, these data may be scarce or inexistent, hindering the overall process.

A Comparative Analysis of Explainable Artificial Intelligence Models for Electric Field Strength Prediction over Eight European Cities.

The widespread propagation of wireless communication devices, from smartphones and tablets to Internet of Things (IoT) systems, has become an integral part of modern life. However, the expansion of wireless technology has also raised public concern about the potential health risks associated with prolonged exposure to electromagnetic fields. Our objective is to determine the optimal machine learning model for constructing electric field strength maps across urban areas, enhancing the field of environmental monitoring with the aid of sensor-based data collection.

Sensors and Advanced Sensing Techniques for Computer Vision Applications.

Computer vision is a multidisciplinary field that enables machines to interpret and understand visual information from the world, simulating human vision [...

Emerging Trends in the Management of Gastric Malignancy with Peritoneal Dissemination: Same Disease, Heterogeneous Prognosis.

Gastric cancer is a significant global contributor to cancer-related mortality. Stage IV gastric cancer represents a significant percentage of patients in Western countries, with peritoneal dissemination being the most prevalent site. Peritoneal disease comprises two distinct entities, macroscopic (P1) and microscopic (P0CY1), which are associated with poor long-term survival rates.

Updates on Imaging of Common Urogenital Neoplasms.

Urogenital neoplasms represent some of the most common malignancies [...

The Thermal Ablation with MRgFUS: From Physics to Oncological Applications.

The growing interest in minimal and non-invasive therapies, especially in the field of cancer treatment, highlights a significant shift toward safer and more effective options. Ablative therapies are well-established tools in cancer treatment, with known effects including locoregional control, while their role as modulators of the systemic immune response against cancer is emerging. The HIFU developed with magnetic resonance imaging (MRI) guidance enables treatment precision, improves real-time procedural control, and ensures accurate outcome assessment.

Deep Learning for Melanoma Detection: A Deep Learning Approach to Differentiating Malignant Melanoma from Benign Melanocytic Nevi.

: Melanoma, an aggressive form of skin cancer, accounts for a significant proportion of skin-cancer-related deaths worldwide. Early and accurate differentiation between melanoma and benign melanocytic nevi is critical for improving survival rates but remains challenging because of diagnostic variability. Convolutional neural networks (CNNs) have shown promise in automating melanoma detection with accuracy comparable to expert dermatologists.