26 research outputs found

    Talk2Car: Taking Control of Your Self-Driving Car

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    A long-term goal of artificial intelligence is to have an agent execute commands communicated through natural language. In many cases the commands are grounded in a visual environment shared by the human who gives the command and the agent. Execution of the command then requires mapping the command into the physical visual space, after which the appropriate action can be taken. In this paper we consider the former. Or more specifically, we consider the problem in an autonomous driving setting, where a passenger requests an action that can be associated with an object found in a street scene. Our work presents the Talk2Car dataset, which is the first object referral dataset that contains commands written in natural language for self-driving cars. We provide a detailed comparison with related datasets such as ReferIt, RefCOCO, RefCOCO+, RefCOCOg, Cityscape-Ref and CLEVR-Ref. Additionally, we include a performance analysis using strong state-of-the-art models. The results show that the proposed object referral task is a challenging one for which the models show promising results but still require additional research in natural language processing, computer vision and the intersection of these fields. The dataset can be found on our website: http://macchina-ai.eu/Comment: 14 pages, accepted at emnlp-ijcnlp 2019 - Added Talk2Nav Referenc

    Statin exposure and risk of cancer in people with and without HIV infection.

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    OBJECTIVE: To determine whether statin exposure is associated with decreased cancer and mortality risk among persons with HIV (PWH) and uninfected persons. Statins appear to have immunomodulatory and anti-inflammatory effects and may reduce cancer risk, particularly among PWH as they experience chronic inflammation and immune activation. DESIGN: Propensity score-matched cohort of statin-exposed and unexposed patients from 2002 to 2017 in the Veterans Aging Cohort Study (VACS), a large cohort with cancer registry linkage and detailed pharmacy data. METHODS: We calculated Cox regression hazard ratios (HRs) and 95% confidence intervals (CI) associated with statin use for all cancers, microbial cancers (associated with bacterial or oncovirus coinfection), nonmicrobial cancers, and mortality. RESULTS: :The propensity score-matched sample (N?=?47?940) included 23?970 statin initiators (31% PWH). Incident cancers were diagnosed in 1160 PWH and 2116 uninfected patients. Death was reported in 1667 (7.0%) statin-exposed, and 2215 (9.2%) unexposed patients. Statin use was associated with 24% decreased risk of microbial-associated cancers (hazard ratio 0.76; 95% CI 0.69-0.85), but was not associated with nonmicrobial cancer risk (hazard ratio 1.00; 95% CI 0.92-1.09). Statin use was associated with 33% lower risk of death overall (hazard ratio 0.67; 95% CI 0.63-0.72). Results were similar in analyses stratified by HIV status, except for non-Hodgkin lymphoma where statin use was associated with reduced risk (hazard ratio 0.56; 95% CI 0.38-0.83) for PWH, but not for uninfected (P interaction?=?0.012). CONCLUSION: In both PWH and uninfected, statin exposure was associated with lower risk of microbial, but not nonmicrobial cancer incidence, and with decreased mortality

    Development and Validation of a Risk Score for Chronic Kidney Disease in HIV Infection Using Prospective Cohort Data from the D:A:D Study

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    Ristola M. on työryhmien DAD Study Grp ; Royal Free Hosp Clin Cohort ; INSIGHT Study Grp ; SMART Study Grp ; ESPRIT Study Grp jäsen.Background Chronic kidney disease (CKD) is a major health issue for HIV-positive individuals, associated with increased morbidity and mortality. Development and implementation of a risk score model for CKD would allow comparison of the risks and benefits of adding potentially nephrotoxic antiretrovirals to a treatment regimen and would identify those at greatest risk of CKD. The aims of this study were to develop a simple, externally validated, and widely applicable long-term risk score model for CKD in HIV-positive individuals that can guide decision making in clinical practice. Methods and Findings A total of 17,954 HIV-positive individuals from the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study with >= 3 estimated glomerular filtration rate (eGFR) values after 1 January 2004 were included. Baseline was defined as the first eGFR > 60 ml/min/1.73 m2 after 1 January 2004; individuals with exposure to tenofovir, atazanavir, atazanavir/ritonavir, lopinavir/ritonavir, other boosted protease inhibitors before baseline were excluded. CKD was defined as confirmed (>3 mo apart) eGFR In the D:A:D study, 641 individuals developed CKD during 103,185 person-years of follow-up (PYFU; incidence 6.2/1,000 PYFU, 95% CI 5.7-6.7; median follow-up 6.1 y, range 0.3-9.1 y). Older age, intravenous drug use, hepatitis C coinfection, lower baseline eGFR, female gender, lower CD4 count nadir, hypertension, diabetes, and cardiovascular disease (CVD) predicted CKD. The adjusted incidence rate ratios of these nine categorical variables were scaled and summed to create the risk score. The median risk score at baseline was -2 (interquartile range -4 to 2). There was a 1: 393 chance of developing CKD in the next 5 y in the low risk group (risk score = 5, 505 events), respectively. Number needed to harm (NNTH) at 5 y when starting unboosted atazanavir or lopinavir/ritonavir among those with a low risk score was 1,702 (95% CI 1,166-3,367); NNTH was 202 (95% CI 159-278) and 21 (95% CI 19-23), respectively, for those with a medium and high risk score. NNTH was 739 (95% CI 506-1462), 88 (95% CI 69-121), and 9 (95% CI 8-10) for those with a low, medium, and high risk score, respectively, starting tenofovir, atazanavir/ritonavir, or another boosted protease inhibitor. The Royal Free Hospital Clinic Cohort included 2,548 individuals, of whom 94 individuals developed CKD (3.7%) during 18,376 PYFU (median follow-up 7.4 y, range 0.3-12.7 y). Of 2,013 individuals included from the SMART/ESPRIT control arms, 32 individuals developed CKD (1.6%) during 8,452 PYFU (median follow-up 4.1 y, range 0.6-8.1 y). External validation showed that the risk score predicted well in these cohorts. Limitations of this study included limited data on race and no information on proteinuria. Conclusions Both traditional and HIV-related risk factors were predictive of CKD. These factors were used to develop a risk score for CKD in HIV infection, externally validated, that has direct clinical relevance for patients and clinicians to weigh the benefits of certain antiretrovirals against the risk of CKD and to identify those at greatest risk of CKD.Peer reviewe

    MTI-Net: Multi-scale task interactions networks for multi-task learning

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