TED Talk Recommender Using Speech Transcripts

Nowadays, online video platforms mostly recommend related videos by analyzing user-driven data such as viewing patterns, rather than the content of the videos. However, content is more important than any other element when videos aim to deliver knowledge. Therefore, we have developed a web application which recommends related TED lecture videos to the users, considering the content of the videos from the transcripts. TED Talk Recommender constructs a network for recommending videos that are similar content-wise and providing a user interface.Comment: 3 page

Combination therapy of vitamin C and thiamine for septic shock in a multicentre, double-blind, randomized, controlled study (ATESS): study protocol for a randomized controlled trial

Background Septic shock is a life-threatening condition with underlying circulatory and cellular/metabolic abnormalities. Vitamin C and thiamine are potential candidates for adjunctive therapy; they are expected to improve outcomes based on recent experimental and clinical research. The aim of the Ascorbic Acid and Thiamine Effect in Septic Shock (ATESS) trial is to evaluate the effects of early combination therapy with intravenous vitamin C and thiamine on recovery from organ failure in patients with septic shock. Methods This study is a randomized, double-blind, placebo-controlled, multicentre trial in adult patients with septic shock recruited from six emergency departments in South Korea. Patients will be randomly allocated into the treatment or control group (1:1 ratio), and we will recruit 116 septic shock patients (58 per group). For the treatment group, vitamin C (50 mg/kg) and thiamine (200 mg) will be mixed in 50 ml of 0.9% saline and administered intravenously every 12 h for a total of 48 h. For the placebo group, an identical volume of 0.9% saline will be administered in the same manner. The primary outcome is the delta Sequential Organ Failure Assessment (SOFA) score (ΔSOFA = initial SOFA at enrolment – follow-up SOFA after 72 h). Discussion This trial will provide valuable evidence about the effectiveness of vitamin C and thiamine therapy for septic shock. If effective, this therapy might improve survival and become one of the main therapeutic adjuncts for patients with septic shock. Trial registration ClinicalTrials.gov, NCT03756220. Registered on 5 December 2018.This work was supported by a National Research Foundation of Korea grant funded by the Korean government (No. 2018R1C1B6006821). The government did not have any role in the study design; collection, management, analysis, and interpretation of data; writing of the report; and the decision to submit the report for publication

Denoising Recurrent Neural Networks for Classifying Crash-Related Events

With detailed sensor and visual data from automobiles, a data-driven model can learn to classify crash-related events during a drive. We propose a neural network model accepting time-series vehicle sensor data and forward-facing videos as input for learning classification of crash-related events and varying types of such events. To elaborate, a novel recurrent neural network structure is introduced, namely, denoising gated recurrent unit with decay, in order to deal with time-series automobile sensor data with missing value and noises. Our model detects crash and near-crash events based on a large set of time-series data collected from naturalistic driving behavior. Furthermore, the model classifies those events involving pedestrians, a vehicle in front, or a vehicle on either side. The effectiveness of our model is evaluated with more than two thousand 30-s clips from naturalistic driving behavior data. The results show that the model, including sensory encoder with denoising gated recurrent unit with decay, visual encoder, and attention mechanism, outperforms gated recurrent unit with decay, gated CNN, and other baselines not only in event classification and but also in event-type classification

Two-Step Question Retrieval for Open-Domain QA

The retriever-reader pipeline has shown promising performance in open-domain QA but suffers from a very slow inference speed. Recently proposed question retrieval models tackle this problem by indexing question-answer pairs and searching for similar questions. These models have shown a significant increase in inference speed, but at the cost of lower QA performance compared to the retriever-reader models. This paper proposes a two-step question retrieval model, SQuID (Sequential Question-Indexed Dense retrieval) and distant supervision for training. SQuID uses two bi-encoders for question retrieval. The first-step retriever selects top-k similar questions, and the second-step retriever finds the most similar question from the top-k questions. We evaluate the performance and the computational efficiency of SQuID. The results show that SQuID significantly increases the performance of existing question retrieval models with a negligible loss on inference speed.Comment: ACL2022-Finding

Massively parallel evaluation and computational prediction of the activities and specificities of 17 small Cas9s

Recently, various small Cas9 orthologs and variants have been reported for use in in vivo delivery applications. Although small Cas9s are particularly suited for this purpose, selecting the most optimal small Cas9 for use at a specific target sequence continues to be challenging. Here, to this end, we have systematically compared the activities of 17 small Cas9s for thousands of target sequences. For each small Cas9, we have characterized the protospacer adjacent motif and determined optimal single guide RNA expression formats and scaffold sequence. High-throughput comparative analyses revealed distinct high- and low-activity groups of small Cas9s. We also developed DeepSmallCas9, a set of computational models predicting the activities of the small Cas9s at matched and mismatched target sequences. Together, this analysis and these computational models provide a useful guide for researchers to select the most suitable small Cas9 for specific applications. © 2023, The Author(s), under exclusive licence to Springer Nature America, Inc.11Nsciescopu

Impact of Insurance Benefits and Education on Point-of-Care Ultrasound Use in a Single Emergency Department: An Interrupted Time Series Analysis

Background and Objectives: Point-of-care ultrasound (POCUS) is a useful tool that helps clinicians properly treat patients in emergency department (ED). This study aimed to evaluate the impact of specific interventions on the use of POCUS in the ED. Materials and Methods: This retrospective study used an interrupted time series analysis to assess how interventions changed the use of POCUS in the emergency department of a tertiary medical institute in South Korea from October 2016 to February 2021. We chose two main interventions—expansion of benefit coverage of the National Health Insurance (NHI) for emergency ultrasound (EUS) and annual ultrasound educational workshops. The primary variable was the EUS rate, defined as the number of EUS scans per 1000 eligible patients per month. We compared the level and slope of EUS rates before and after interventions. Results: A total of 5188 scanned records were included. Before interventions, the EUS rate had increased gradually. After interventions, except for the first workshop, the EUS rate immediately increased significantly (p < 0.05). The difference in the EUS rate according to the expansion of the NHI was estimated to be the largest (p < 0.001). However, the change in slope significantly decreased after the third workshop during the coronavirus disease 2019 pandemic (p = 0.004). The EUS rate increased significantly in the presence of physicians participating in intensive POCUS training (p < 0.001). Conclusion: This study found that expansion of insurance coverage for EUS and ultrasound education led to a significant and immediate increase in the use of POCUS, suggesting that POCUS use can be increased by improving education and insurance benefits