Incorporating LLM Priors into Tabular Learners

We present a method to integrate Large Language Models (LLMs) and traditional tabular data classification techniques, addressing LLMs challenges like data serialization sensitivity and biases. We introduce two strategies utilizing LLMs for ranking categorical variables and generating priors on correlations between continuous variables and targets, enhancing performance in few-shot scenarios. We focus on Logistic Regression, introducing MonotonicLR that employs a non-linear monotonic function for mapping ordinals to cardinals while preserving LLM-determined orders. Validation against baseline models reveals the superior performance of our approach, especially in low-data scenarios, while remaining interpretable.Comment: Table Representation Learning Workshop at NeurIPS 202

Comparison of Collocation Extraction Measures for Document Indexing

Automatic extraction of collocations from a corpus is a well-known problem in the field of natural language processing. It is typically carried out by employing some kind of a statistical measure that indicates whether or not two words occur together more often than by chance. As there is an aboundance of these measures proposed by various authors, we have compared some of them on a task of extracting collocations from a corpus of Croatian legal documents for the purpose of document indexing. We propose and evaluate extensions of these measures for collocations consisting of three words

Hepatitis B Outbreak Among Men Who Have Sex with Men in the Autonomous Province of Vojvodina, Serbia

** From Crossref via Jisc Publications Router.The European Centre for Disease Prevention and Control reported that there were 2896 acute hepatitis B cases in 24 EU/EEA countries in 2013.1 The incidence ranged from 0.1 cases per 100,000 in France and Portugal to 4.3 per 100,000 in Latvia, with a male-to-female ratio of 2.2:1 in EU/EEA countries, and transmission among men who have sex with men (MSM) reported in 9.4% of all cases of acute hepatitis B.1 Some authors consider hepatitis B virus (HBV) infection to be endemic in the MSM population with the incidence 20 times higher in MSM than in the general population worldwide.2 However, data on HBV prevalence among MSM are available for only four EU/EEA countries.3 Six to ten percent of MSM infected with HBV worldwide are co-infected with HIV.4sch_iih5pub4999pub

Clinical Presentation and Management of Methicillin-Resistant Staphylococcus aureus Pericarditis—Systematic Review

In the expanding era of antibiotic resistance, new strains of Staphylococcus aureus have emerged which possess resistance to traditionally used antibiotics (MRSA). Our review aimed to systematically synthesize information on previously described MRSA pericarditis cases. The only criterion for inclusion was the isolation of MRSA from the pericardial space. Our review included 30 adult and 9 pediatric patients (aged: 7 months to 78 years). Comorbid conditions were seen in most adult patients, whereas no comorbidities were noted amongst the pediatric patients. Pericardial effusion was found in 94.9% of cases, with evidence of tamponade in 83.8%. All cases isolated MRSA from pericardial fluid and 25 cases (64.1%) had positive blood cultures for MRSA. Pericardiocentesis and antibiotics were used in all patients. The mortality rate amongst adults was 20.5%, with a mean survival of 21.8 days, and attributed to multi-organ failure associated with septic shock. No mortality was observed in the pediatric population. In adult patients, there was no statistical difference in symptom duration, antibiotic duration, presence of tamponade, age, and sex in relation to survival. Conclusion: MRSA pericarditis often presents with sepsis and is associated with significant mortality. As such, a high clinical suspicion is needed to proceed with proper tests such as echocardiography and pericardiocentesis. In more than one third of the cases, MRSA pericarditis occurs even in the absence of documented bacteremia

Introducing Open Data Concepts to STEM Students Using Real-World Open Datasets

While open data concepts become more important in our society, education about its benefits and technical issues is still behind the practice. Students of STEM disciplines should be introduced to open data during their education. The Open Computing course, completely redesigned in the new Computing curriculum, introduces open data concepts, providing both the basics and advanced topics, from technical to social and legal viewpoints. Among the several educational activities, one was particularly useful for understanding the needs and implications of using open data: a synchronous group activity where students had to choose a societal issue, find and analyze two open datasets that would help gaining insight into this issue, assess interdisciplinarity approaches and stakeholders, and finally propose the added value emerging from the solution. In a short amount of time needed, this activity - which tackled multiple aspects of the problem - brought a clearer insight into the topic, building upon the conventional lectures. Students highly graded such an approach to their education, where they had to construct their knowledge by the group experience. A similar group activity appeared to be useful in the con of open data PhD training and might also be used in other disciplines and domains.</p