Clinical prediction models are often based solely on the use of structured data in electronic health records, e.g. vital parameters and laboratory results, effectively ignoring potentially valuable information recorded in other modalities, such as freetext clinical notes. Here, we report on the development of a multimodal model that combines structured and unstructured data. In particular, we study how best to make use of a clinical language model in a multimodal setup for predicting 30-day all-cause mortality upon hospital admission in patients with COVID-19. We evaluate three strategies for incorporating a domain-specific clinical BERT model in multimodal prediction systems: (i) without fine-tuning, (ii) with unimodal fine-tuning, and (iii) with multimodal fine-tuning. The best-performing model leverages multimodal fine-tuning, in which the clinical BERT model is updated based also on the structured data. This multimodal mortality prediction model is shown to outperform unimodal models that are based on using either only structured data or only unstructured data. The experimental results indicate that clinical prediction models can be improved by including data in other modalities and that multimodal fine-tuning of a clinical language model is an effective strategy for incorporating information from clinical notes in multimodal prediction systems.
This study represents use of EPANET software in the design of water distribution network. EPANET software is a user friendly software. In order to ensure the availability of sufficient quantity of good quality of water to the various section of community in accordance with the demand, many computer tools were developed, out of all the tools available EPANET become most popular and convenient for the effective design of complex pipe networks. This paper highlights only the effective design and distribution of network of pipes using EPANET tool. The residual head at each and every node was found out by having the elevation as input and thereby the corresponding flow quantities were derived like residual head, velocity and nodal demand etc.
Earthquakes are natural trouble under which disasters are mainly caused by damage or collapse of the structure and other man-made structures. When an earthquake occurs natural period of vibration is more on heavy loaded building and less in light loaded building. If the building is light weighted, i.e. steel is less then economy of structure is also achieved. Hence it is necessary to find out natural/fundamental time period when mass changes with different type of brick masonry and concrete masonry.This is necessary because IS 1893:2002 does not incorporate the effect of mass in a formula which they have mentioned for brick masonary structure. Thedesign will also analyze with ETAB software.
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