Objectives To prospectively investigate in patients with severe COVID-19-associated cytokine storm syndrome (CSS) whether an intensive course of glucocorticoids or without tocilizumab accelerates clinical improvement, reduces mortality and prevents invasive mechanical ventilation, comparison a historic control group who received supportive care only. Methods From 1 April 2020, CSS, defined as rapid respiratory deterioration plus at least two out three biomarkers important elevations...

In clinical practice, non-medical switching of biological medication may provoke nocebo effects due to unexplained deterioration therapeutic benefits. Indication extrapolation, idiosyncratic reactions, and interchangeability remain challenged in practice after biosimilar approval by the European Medicines Agency. The principle "first do no harm" be a patient when from originator biological. To describe 1-year results pragmatic study on infliximab implementation immune-mediated inflammatory...

A current research question in the area of entity resolution (also called link discovery or duplicate detection) is whether and which cases embeddings deep neural network based matching methods outperform traditional symbolic methods. The problem with answering this that learning matchers need large amounts training data. benchmark datasets are currently available to public too small properly evaluate new family WDC Training Dataset for Large-Scale Product Matching fills gap. English...

An increasing number of data providers have adopted shared numbering schemes such as GTIN, ISBN, DUNS, or ORCID numbers for identifying entities in the respective domain. This means integration that identifiers are often available a subset entity descriptions to be integrated while not others. The challenge these settings is learn matcher without using containing training data. task can approached by learning binary classifier which distinguishes pairs same real-world from different...

Contrastive learning has moved the state of art for many tasks in computer vision and information retrieval recent years. This poster is first work that applies supervised contrastive to task product matching e-commerce using offers from different e-shops. More specifically, we employ a technique pre-train Transformer encoder which afterward fine-tuned pair-wise training data. We further propose source-aware sampling strategy enables be applied use cases data does not contain identifiers....

COVID-19 is a novel viral disease caused by SARS-CoV-2. The mid- and long-term outcomes have not yet been determined. infection increasingly being associated with systemic multi-organ involvement, encompassing cytokine release syndrome thromboembolic, vascular cardiac events. patient described experienced unusually rapid development of pulmonary hypertension (PH) right ventricular failure after recent severe pneumonia syndrome, which initially was successfully treated methylprednisolone...

Objective To test the longitudinal association between patient-reported outcome, Routine Assessment of Patient Index Data 3 (RAPID3) and Disease Activity Score in 28 joints that includes erythrocyte sedimentation rate (DAS28-ESR) routine-care patients with rheumatoid arthritis (RA). Methods Patients RA treated disease-modifying antirheumatic drugs were included this prospective observational cohort. The RAPID3 (0–10) DAS28-ESR its individual components (swollen joint count (SJC), (ESR)...

To explore in elderly patients with rheumatoid arthritis (RA) and comorbidity (1) which order why prioritize their morbidities regard to functioning health, (2) beliefs about common (age-related) musculoskeletal complaints, (3) experiences the influence of on medication treatment RA. Patients between 50 85 years RA ≥ 1 or lifestyle risk factor were invited for a semi-structured interview. Two readers coded transcripts interviews, by using NVivo11 software. Fifteen (14 women; mean age 67...

In this qualitative study we analyzed the (1) influence of age, comorbidity, and frailty on management goals in elderly patients with RA; (2) experiences rheumatologists regarding use Disease Activity Score at 28 joints (DAS28) to monitor disease activity; (3) differences strategies RA compared their younger counterparts.Rheumatologists were purposively sampled for a semistructured interview. Two readers independently read coded interview transcripts. Important concepts taxonomically...

The difficulty of an entity matching task depends on a combination multiple factors such as the amount corner-case pairs, fraction entities in test set that have not been seen during training, and size development set. Current benchmarks usually represent single points space along dimensions or they provide for evaluation methods dimension, instance training data. This paper presents WDC Products, benchmark which provides systematic systems combinations three while relying real-world are (i)...

Generative large language models (LLMs) are a promising alternative to pre-trained for entity matching due their high zero-shot performance and ability generalize unseen entities. Existing research on using LLMs has focused prompt engineering in-context learning. This paper explores the potential of fine-tuning matching. We analyze along two dimensions: 1) The representation training examples, where we experiment with adding different types LLM-generated explanations set, 2) selection...

Product matching is a central task within e-commerce applications such as price comparison portals and online market places. State-of-the-art product methods achieve F1 scores above 0.90 using deep learning techniques combined with huge amounts of training data (e.g > 100K pairs offers). Gathering maintaining large corpora costly, it implies labeling offers matches or non-matches. Acquiring the ability to be good at thus means major investment for an company. This paper shows that manual can...

We aim to evaluate the clinical pharmacokinetics of a single dose interleukin-6 (IL-6) antibody tocilizumab (TCZ) in methylprednisolone (MP)-treated COVID-19 patients with cytokine storm syndrome (CSS).

Entity Matching is the task of deciding if two entity descriptions refer to same real-world entity. State-of-the-art matching methods often rely on fine-tuning Transformer models such as BERT or RoBERTa. Two major drawbacks using these for are that (i) require significant amounts data reaching a good performance and (ii) fine-tuned not robust concerning out-of-distribution entities. In this paper, we investigate ChatGPT more robust, training data-efficient alternative traditional models. We...

Entity Matching is the task of deciding whether two entity descriptions refer to same real-world entity. It a central step in most data integration pipelines and an enabler for many e-commerce applications which require match products offers from different vendors. State-of-the-art matching methods rely on pre-trained language models (PLMs) such as BERT or RoBERTa. Two major drawbacks these are that (i) significant amounts task-specific training (ii) fine-tuned not robust concerning...

We aimed to evaluate the effects of methotrexate (MTX) comedication added biological disease-modifying antirheumatic drugs (bDMARD) on disease activity measures in patients with rheumatoid arthritis (RA) routine care.Patients RA treatment either bDMARDs or conventional synthetic DMARDs were included this prospective cohort study. The effect (time-varying) combination therapy bDMARD and MTX compared monotherapy was tested longitudinal generalised estimating equation models using as outcomes:...

Transformer-based entity matching methods have significantly moved the state of art for less-structured tasks such as product offers in e-commerce. In order to excel at these tasks, require a decent amount training pairs. Providing enough data can be challenging, especially if matcher non-English descriptions should learned. This poster explores along use case from different e-shops which extent it is possible improve performance matchers by complementing small set pairs target language,...

The research on table representation learning, data retrieval, and integration in the context of lakes requires large corpora for training evaluation developed methods. Over years, several such as WikiTables, GitTables, or Dresden Web Table Corpus have been published are used by community. This paper complements set public with Data Commons Schema.org corpora, two consisting 4.2 (Release 2020) 5 million 2023) relational tables describing products, events, local businesses, job postings,...

<h3>Background</h3> The Routine Assessment of Patient Index Data 3 (RAPID3) is a patient reported outcome (PRO) proposed to conveniently measure disease activity in rheumatoid arthritis (RA) based on functioning, pain and global health scores. DAS28 (including PRO objective measures) the most frequently used score clinical practice research for that purpose^[1]. It has been suggested composite scores measuring PROs only (e.g. RAPID3) might add assessment over time but this claim...