An autonomous debating system.

Artificial intelligence (AI) is defined as the ability of machines to perform tasks that are usually associated with intelligent beings. Argument and debate are fundamental capabilities of human intelligence, essential for a wide range of human activities, and common to all human societies. The development of computational argumentation technologies is therefore an important emerging discipline in AI research1. Here we present Project Debater, an autonomous debating system that can engage in a competitive debate with humans. We provide a complete description of the system's architecture, a thorough and systematic evaluation of its operation across a wide range of debate topics, and a detailed account of the system's performance in its public debut against three expert human debaters. We also highlight the fundamental differences between debating with humans as opposed to challenging humans in game competitions, the latter being the focus of classical 'grand challenges' pursued by the AI research community over the past few decades. We suggest that such challenges lie in the 'comfort zone' of AI, whereas debating with humans lies in a different territory, in which humans still prevail, and for which novel paradigms are required to make substantial progress.

Chatbot-Delivered COVID-19 Vaccine Communication Message Preferences of Young Adults and Public Health Workers in Urban American Communities: Qualitative Study.

BACKGROUND: Automated conversational agents, or chatbots, have a role in reinforcing evidence-based guidance delivered through other media and offer an accessible, individually tailored channel for public engagement. In early-to-mid 2021, young adults and minority populations disproportionately affected by COVID-19 in the United States were more likely to be hesitant toward COVID-19 vaccines, citing concerns regarding vaccine safety and effectiveness. Successful chatbot communication requires purposive understanding of user needs. OBJECTIVE: We aimed to review the acceptability of messages to be delivered by a chatbot named VIRA from Johns Hopkins University. The study investigated which message styles were preferred by young, urban-dwelling Americans as well as public health workers, since we anticipated that the chatbot would be used by the latter as a job aid. METHODS: We conducted 4 web-based focus groups with 20 racially and ethnically diverse young adults aged 18-28 years and public health workers aged 25-61 years living in or near eastern-US cities. We tested 6 message styles, asking participants to select a preferred response style for a chatbot answering common questions about COVID-19 vaccines. We transcribed, coded, and categorized emerging themes within the discussions of message content, style, and framing. RESULTS: Participants preferred messages that began with an empathetic reflection of a user concern and concluded with a straightforward, fact-supported response. Most participants disapproved of moralistic or reasoning-based appeals to get vaccinated, although public health workers felt that such strong statements appealing to communal responsibility were warranted. Responses tested with humor and testimonials did not appeal to the participants. CONCLUSIONS: To foster credibility, chatbots targeting young people with vaccine-related messaging should aim to build rapport with users by deploying empathic, reflective statements, followed by direct and comprehensive responses to user queries. Further studies are needed to inform the appropriate use of user-customized testimonials and humor in the context of chatbot communication.

Usability and Credibility of a COVID-19 Vaccine Chatbot for Young Adults and Health Workers in the United States: Formative Mixed Methods Study.

BACKGROUND: The COVID-19 pandemic raised novel challenges in communicating reliable, continually changing health information to a broad and sometimes skeptical public, particularly around COVID-19 vaccines, which, despite being comprehensively studied, were the subject of viral misinformation. Chatbots are a promising technology to reach and engage populations during the pandemic. To inform and communicate effectively with users, chatbots must be highly usable and credible. OBJECTIVE: We sought to understand how young adults and health workers in the United States assessed the usability and credibility of a web-based chatbot called Vira, created by the Johns Hopkins Bloomberg School of Public Health and IBM Research using natural language processing technology. Using a mixed method approach, we sought to rapidly improve Vira's user experience to support vaccine decision-making during the peak of the COVID-19 pandemic. METHODS: We recruited racially and ethnically diverse young people and health workers, with both groups from urban areas of the United States. We used the validated Chatbot Usability Questionnaire to understand the tool's navigation, precision, and persona. We also conducted 11 interviews with health workers and young people to understand the user experience, whether they perceived the chatbot as confidential and trustworthy, and how they would use the chatbot. We coded and categorized emerging themes to understand the determining factors for participants' assessment of chatbot usability and credibility. RESULTS: In all, 58 participants completed a web-based usability questionnaire and 11 completed in-depth interviews. Most questionnaire respondents said the chatbot was "easy to navigate" (51/58, 88%) and "very easy to use" (50/58, 86%), and many (45/58, 78%) said its responses were relevant. The mean Chatbot Usability Questionnaire score was 70.2 (SD 12.1) and scores ranged from 40.6 to 95.3. Interview participants felt the chatbot achieved high usability due to its strong functionality, performance, and perceived confidentiality and that the chatbot could attain high credibility with a redesign of its cartoonish visual persona. Young people said they would use the chatbot to discuss vaccination with hesitant friends or family members, whereas health workers used or anticipated using the chatbot to support community outreach, save time, and stay up to date. CONCLUSIONS: This formative study conducted during the pandemic's peak provided user feedback for an iterative redesign of Vira. Using a mixed method approach provided multidimensional feedback, identifying how the chatbot worked well-being easy to use, answering questions appropriately, and using credible branding-while offering tangible steps to improve the product's visual design. Future studies should evaluate how chatbots support personal health decision-making, particularly in the context of a public health emergency, and whether such outreach tools can reduce staff burnout. Randomized studies should also be conducted to measure how chatbots countering health misinformation affect user knowledge, attitudes, and behavior.

Predicting bloodstream infection outcome using machine learning.

Bloodstream infections (BSI) are a main cause of infectious disease morbidity and mortality worldwide. Early prediction of BSI patients at high risk of poor outcomes is important for earlier decision making and effective patient stratification. We developed electronic medical record-based machine learning models that predict patient outcomes of BSI. The area under the receiver-operating characteristics curve was 0.82 for a full featured inclusive model, and 0.81 for a compact model using only 25 features. Our models were trained using electronic medical records that include demographics, blood tests, and the medical and diagnosis history of 7889 hospitalized patients diagnosed with BSI. Among the implications of this work is implementation of the models as a basis for selective rapid microbiological identification, toward earlier administration of appropriate antibiotic therapy. Additionally, our models may help reduce the development of BSI and its associated adverse health outcomes and complications.

Oesophageal sarcomas in dogs: histological and clinical evaluation.

A histological grading system of oesophageal sarcomas has not been established. Thirty-two cases of oesophageal sarcomas have been reviewed for tumour characteristics and clinical outcome. Nineteen dogs underwent surgical intervention to remove oesophageal tumours; ten of them survived (median 278 days). Primary tumour types included osteosarcoma (47%), osteosarcoma with tumour giant cells (7%), fibroblastic osteosarcoma (13%), chondroblastic osteosarcoma (7%) fibrosarcoma (23%) and undifferentiated sarcoma (3%). Histological grade evaluation revealed 33% grade 1 sarcoma, 50% grade 2 and 17% grade 3. No correlation could be found between survival and signalment, duration of clinical signs, tumour type, tumour grade and chemotherapy. Chemotherapy was found to reduce lung metastases' histological scores in three cases (P=0.0007). Surgery seems to be the treatment of choice but the effect of chemotherapy warrants further investigation. Additional research of cases should be performed in order to further define prognostic factors of oesophageal sarcomas.

Transcytosis of Streptococcus iniae through skin epithelial barriers: an in vitro study.

By constructing a biological model based on in vitro culture of polarized rainbow trout primary skin epithelial cell monolayers, the series of early events that precede Streptococcus iniae infection, particularly colonization and translocation through external barriers, were analyzed. Streptococcus iniae promptly invades skin epithelial cells, but the rapid decline of viable intracellular bacteria points out the limited capability of intracellular survival for this bacterium. Translocation assays, supported by electron microscopy microphotographs, demonstrate that following successful in vitro invasion of skin epithelial cell, the bacterium exists free in the cytoplasm after release from the endosome, and translocates through the skin barrier. Bacterial invasion and transcytosis is not accompanied by apparent cell-line damages or disruption of host cells' tight junctions. It is hypothesized that the phenomenon of epithelial invasion coupled to the rapid translocation through the barrier plays a crucial role in Streptococcus iniae infection.

Experimental infection of common garter snakes (Thamnophis sirtalis) with West Nile virus.

The role of various reptilian species in the infectious cycle of several arboviruses is documented, but their role in that of West Nile virus (WNV) is uncertain. Common garter snakes (Thamnophis sirtalis) were infected subcutaneously with 10(5) plaque forming units (PFU) WNV-Isr 98, five of nine snakes became viremic, and five exhibited persistent low levels of neutralizing antibodies. Four of the parentally infected snakes died and high titers of virus were found in multiple organ samples. In contrast, orally infected garter snakes did not become viremic, but viral RNA was detected in cloacal swabs. Since oral infection of predator birds by WNV is known, their ingestion of infected snakes may also result in their becoming infected.

Bovine necrotic vulvovaginitis associated with Porphyromonas levii.

An outbreak of bovine necrotic vulvovaginitis associated with Porphyromonas levii, an emerging animal and human pathogen, affected 32 cows on a dairy farm in the northeast of Israel. Five animals had to be culled. This report appears to be the first that associates P. levii with bovine necrotic vulvovagnitis.