LinkedIn . ... Washington, District of Columbia 20005 (202) 760-3208 (office) (202) 760-3191 (fax) Additional Info. After identifying and removing batch effects between the two groups, we trained an ℓ1-regularized logistic regression classifier to predict ASD status from each set of variants. Prior to this, he completed a MS in CS at Stanford University (where he contributed UX work to the Autism Glass Project) and a BA in CS at Rice University. View details for DOI 10.2196/13668 The intervention reinforces facial engagement and emotion recognition, suggesting either or both could be a mechanism of action driving the observed improvement. I suppose that’s what drew me to spend a quarter researching the modern American political system. Washington, P., Leblanc, E., Dunlap, K., Penev, Y., Kline, A., Paskov, K., Sun, M. W., Chrisman, B., Stockham, N., Varma, M., Voss, C., Haber, N., Wall, D. P. Game theoretic centrality: a novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value. BIOE 141A: Senior Capstone Design I (Autumn). Peter Boshard has 7 jobs listed on their profile. The 2019 Stanford Cardinal football team represented Stanford University in the 2019 NCAA Division I FBS football season. Ziaire Williams finished with 12 points, 12 rebounds and 10 assists to become just the second player in Cardinal history to record a triple-double. Ning, M., Daniels, J., Schwartz, J., Dunlap, K., Washington, P., Kalantarian, H., Du, M., Wall, D. P. Scientific Discovery Games for Biomedical Research. We recruited 21 children with ASD to play the game and gathered 2602 emotive frames following their game sessions. Peter has 4 jobs listed on their profile. Rethinking the Imaging Pipeline for Energy‐Efficient Privacy‐Preserving Continuous Mobile Vision. The Latest: Pac-12 cancels Washington State-Stanford game. This pilot exploratory study examines our prototype tool's potential for social-affective learning for children with autism. To understand this, we focus on the effects of changing the robots' speed, sm... With most recent estimates giving an incidence rate of 1 in 68 children in the United States, the autism spectrum disorder (ASD) is a growing public health crisis. View Peter Washington’s profile on LinkedIn, the world’s largest professional community. Assessments were completed at the Stanford University Medical School, and enrolled participants used the Superpower Glass intervention in their homes. Our results show the importance of the noncoding region and the utility of independent control groups in effectively linking genetic variation to disease phenotype for complex disorders. PMID: 32823538 DOI: 10.3390/jpm10030086 Abstract Mobilized telemedicine is becoming a key, and even necessary, facet of both precision health and precision medicine. The goal is to have non-scientists discover life at the microscopic level, experiment with the tools and mechanisms at hand -lenses, growth medium, systems to get the cells to move -, find out facts about these microorganisms by themselves, develop their curiosity, and start discussing with scientists. A repeated-measures one-way ANOVA demonstrated a decrease in SRS-2 total scores by an average 7.14 points (F(1,13) = 33.20, p =  Stanford freshman forward Ziaire Williams drives past Washington’s Jamal Bey to score for the Cardinal during the first half at Kaiser Permanente Arena in Santa Cruz on Thursday. Peter Washington is part of Stanford Profiles, official site for faculty, postdocs, students and staff information (Expertise, Bio, Research, Publications, and more). Autism spectrum disorder (ASD) is currently diagnosed using qualitative methods that measure between 20-100 behaviors, can span multiple appointments with trained clinicians, and take several hours to complete. Finally, we summarize existing digital therapeutic interventions that allow for data capture and longitudinal outcome tracking as the diagnosis moves along a positive trajectory. However, these classifiers are trained on datasets of predominantly neurotypical adults and can sometimes fail to generalize to children with autism. Activity recognition computer vision algorithms can be used to detect the presence of autism-related behaviors, including what are termed "restricted and repetitive behaviors", or stimming, by diagnostic instruments. However, nearly unavoidable variability in video quality can lead to missing features that degrade algorithm performance. Choose between 25+ different decks and … This work informs the design of programming environments for controlling living matter in general, for living material microfabrication and swarm robotics applications, and for lowering the access barriers to the life sciences for professional and citizen scientists, learners, and the lay public. States with the highest diagnostic resource load included West Virginia, Kentucky, Maine, Mississippi, and New Mexico.Results from this study demonstrate the sparsity and uneven distribution of diagnostic resources in the United States, which may contribute to the lengthy waitlists and travel distances-barriers to be overcome to be able to receive diagnosis in specific regions. Emotion classification algorithms are receiving increasing interest in digital therapies, but existing approaches may not be designed for pediatric populations. Due in part to increasing prevalence, access to treatment has become constrained. The limited data that exist in this domain are usually recorded with a handheld camera which can be shaky or even moving, posing a ch... Current emotion detection classifiers predict discrete emotions. BACKGROUND: Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social communication and interaction, and restricted and repetitive behaviors and interests. Dr. ... Their recent gifts include endowment of the Bing Stanford in Washington Program and Bing Overseas Studies Program. 1 in 59 children have autism. Genetic analyses of ASD typically use unaffected family members as controls; however, we hypothesize that this method does not effectively elevate variant signal in the noncoding region due to family members having subclinical phenotypes arising from common genetic mechanisms. Using sequences from the GISAID database, we... Mobilized telemedicine is becoming a key, and even necessary, facet of both precision health and precision medicine. We feed worker responses as input to a validated diagnostic machine learning classifier trained on clinician-filled electronic health records. Positive mean treatment effects were also found for the other 3 primary measures but not to a significance threshold of P=.0125.Conclusions and Relevance: The observed 4.58-point average gain on the Vineland Adaptive Behaviors Scale socialization subscale is comparable with gains observed with standard of care therapy. For Study 2, the mean score of the participants rating new videos was 6.76/10 (SD 0.59). Importance: Autism behavioral therapy is effective but expensive and difficult to access. Crowdsourcing approaches may provide a scalable alternative that can accelerate general access to care and permit underserved populations to obtain an accurate diagnosis.OBJECTIVE: We aimed to perform a series of studies to explore whether paid crowd workers on Amazon Mechanical Turk (AMT) and citizen crowd workers on a public website shared on social media can provide accurate online detection of autism, conducted via crowdsourced ratings of short home video clips.METHODS: Three online studies were performed: (1) a paid crowdsourcing task on AMT (N=54) where crowd workers were asked to classify 10 short video clips of children as "Autism" or "Not autism," (2) a more complex paid crowdsourcing task (N=27) with only those raters who correctly rated ≥8 of the 10 videos during the first study, and (3) a public unpaid study (N=115) identical to the first study.RESULTS: For Study 1, the mean score of the participants who completed all questions was 7.50/10 (SD 1.46). The Indians led by sixth-year head coach John Ralston. We then apply face tracking and emotion recognition algorithms to videos acquired through Guess What? We also determine Shapley values for the most important features in the classifier to understand how the classifiers' process aligns with clinical intuition.Using these techniques, we achieved an accuracy (area under the curve [AUC]) of 76% (SD 3%) and sensitivity of 76% (SD 4%) for identifying atypical children from among developmentally delayed children, and an accuracy (AUC) of 85% (SD 5%) and sensitivity of 76% (SD 6%) for identifying children with ASD from those predicted to have other developmental delays.These results show promise for using a mobile video-based and machine learning-directed approach for early and remote detection of autism in Bangladeshi children. The standard approaches to diagnosing autism spectrum disorder (ASD) evaluate between 20 and 100 behaviors and take several hours to complete. 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