169 research outputs found
Enhancing asynchronous user communication with cross platform and channel agnostic messaging services
Enhancing Asynchronous User Communication with Cross Platform and Channel Agnostic Messaging Services
EXECUTABLE ARCHIVES: Software integrity for data readability and validation of archived studies
© 2021 author(s). The text of this paper is published under a CC-BY license (https://creativecommons.org/licenses/by/4.0/)This paper presents practices and processes for managing software integrity to support data archiving for long term use in response to the regulatory requirements. Through a case study of a scientific software decommissioning, we revisit the issues of archived data readability. Established software lifecycle management processes are extended with archiving and data integrity requirements for retention of data and revalidation of data analyses. That includes the software transition from operational to archival use within the Executable Archive model that extends the traditional data archive with computing environments with software installations required to reproduce study results from the archived records. The content use requirements are an integral part of both data access and the software management considerations, assuring that data integrity is fully supported by the software integrityPeer reviewe
Contextual Knowledge Learning For Dialogue Generation
Incorporating conversational context and knowledge into dialogue generation
models has been essential for improving the quality of the generated responses.
The context, comprising utterances from previous dialogue exchanges, is used as
a source of content for response generation and as a means of selecting
external knowledge. However, to avoid introducing irrelevant content, it is key
to enable fine-grained scoring of context and knowledge. In this paper, we
present a novel approach to context and knowledge weighting as an integral part
of model training. We guide the model training through a Contextual Knowledge
Learning (CKL) process which involves Latent Vectors for context and knowledge,
respectively. CKL Latent Vectors capture the relationship between context,
knowledge, and responses through weak supervision and enable differential
weighting of context utterances and knowledge sentences during the training
process. Experiments with two standard datasets and human evaluation
demonstrate that CKL leads to a significant improvement compared with the
performance of six strong baseline models and shows robustness with regard to
reduced sizes of training sets.Comment: 9 pages, 4 figures, 6 tables. Accepted as a full paper in the main
conference by ACL 202
Smoking habits, cadmium exposure and vulnerability to chemicals of lung adenocarcinoma male patients in Vojvodina
Thrombotic and bleeding complications in patients with chronic lymphocytic leukemia and severe COVID-19: a study of ERIC, the European Research Initiative on CLL
Edad; Terapia anticoagulante; HemorragiaEdat; TerĂ pia anticoagulant; HemorrĂ giaAge; Anticoagulant therapy; HaemorrhageBackground: Patients with chronic lymphocytic leukemia (CLL) may be more susceptible to COVID-19 related poor outcomes, including thrombosis and death, due to the advanced age, the presence of comorbidities, and the disease and treatment-related immune deficiency. The aim of this study was to assess the risk of thrombosis and bleeding in patients with CLL affected by severe COVID-19.
Methods: This is a retrospective multicenter study conducted by ERIC, the European Research Initiative on CLL, including patients from 79 centers across 22 countries. Data collection was conducted between April and May 2021. The COVID-19 diagnosis was confirmed by the real-time polymerase chain reaction (RT-PCR) assay for SARS-CoV-2 on nasal or pharyngeal swabs. Severe cases of COVID-19 were defined by hospitalization and the need of oxygen or admission into ICU. Development and type of thrombotic events, presence and severity of bleeding complications were reported during treatment for COVID-19. Bleeding events were classified using ISTH definition. STROBE recommendations were used in order to enhance reporting.
Results: A total of 793 patients from 79 centers were included in the study with 593 being hospitalized (74.8%). Among these, 511 were defined as having severe COVID: 162 were admitted to the ICU while 349 received oxygen supplementation outside the ICU. Most patients (90.5%) were receiving thromboprophylaxis. During COVID-19 treatment, 11.1% developed a thromboembolic event, while 5.0% experienced bleeding. Thrombosis developed in 21.6% of patients who were not receiving thromboprophylaxis, in contrast to 10.6% of patients who were on thromboprophylaxis. Bleeding episodes were more frequent in patients receiving intermediate/therapeutic versus prophylactic doses of low-molecular-weight heparin (LWMH) (8.1% vs. 3.8%, respectively) and in elderly. In multivariate analysis, peak D-dimer level and C-reactive protein to albumin ratio were poor prognostic factors for thrombosis occurrence (OR = 1.022, 95%CI 1.007‒1.038 and OR = 1.025, 95%CI 1.001‒1.051, respectively), while thromboprophylaxis use was protective (OR = 0.199, 95%CI 0.061‒0.645). Age and LMWH intermediate/therapeutic dose administration were prognostic factors in multivariate model for bleeding (OR = 1.062, 95%CI 1.017-1.109 and OR = 2.438, 95%CI 1.023-5.813, respectively).
Conclusions: Patients with CLL affected by severe COVID-19 are at a high risk of thrombosis if thromboprophylaxis is not used, but also at increased risk of bleeding under the LMWH intermediate/therapeutic dose administration
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