Concussion Biomarker Discovery For Prognosis In Adolescent Athletes (compete) Pilot Study

Concussion management in the ED is inconsistent due to a lack of available empirical testing. This project aims to assess the feasibility of a large multi-centered study for concussion biomarker discovery in the ED. This prospective cohort pilot and feasibility study was conducted in the adult and pediatric EDs of an urban, academic, Level 1 trauma center. Twelve patients with concussions and twelve age- and gender-matched control patients presenting within 6 hours of an injury sustained during recreational activity were enrolled. ED blood specimens were banked for future proteomic analysis. Clinical outcomes were collected via online survey. Patient recruitment strategies were refined in three phases: (1) identification and notification by clinical staff, (2) email notification automatically-generated by the electronic health record (EHR), and (3) patient financial incentives provided at enrollment and upon completion of the symptom diary. After Phase 1, the patient identification rate improved from 0% to 22% (p\u3c0.001) with EHR-generated notifications. In Phase 3, the enrollment rate improved from 38% to 100% (p=0.01) with financial incentives. This pilot and feasibility project is the first step to toward the goal of identifying new diagnostic and prognostic biomarkers as well as novel targets for therapy. EHR-based paging and financial incentives for participation increased subject identification and enrollment rate to inform and optimize the enrollment and recruitment strategies for the eventual larger study

Proceedings of the SAB'06 Workshop on Adaptive Approaches for Optimizing Player Satisfaction in Computer and Physical Games

These proceedings contain the papers presented at the Workshop on Adaptive approaches for Optimizing Player Satisfaction in Computer and Physical Games held at the Ninth international conference on the Simulation of Adaptive Behavior (SAB’06): From Animals to Animats 9 in Rome, Italy on 1 October 2006. We were motivated by the current state-of-the-art in intelligent game design using adaptive approaches. Artificial Intelligence (AI) techniques are mainly focused on generating human-like and intelligent character behaviors. Meanwhile there is generally little further analysis of whether these behaviors contribute to the satisfaction of the player. The implicit hypothesis motivating this research is that intelligent opponent behaviors enable the player to gain more satisfaction from the game. This hypothesis may well be true; however, since no notion of entertainment or enjoyment is explicitly defined, there is therefore little evidence that a specific character behavior generates enjoyable games. Our objective for holding this workshop was to encourage the study, development, integration, and evaluation of adaptive methodologies based on richer forms of humanmachine interaction for augmenting gameplay experiences for the player. We wanted to encourage a dialogue among researchers in AI, human-computer interaction and psychology disciplines who investigate dissimilar methodologies for improving gameplay experiences. We expected that this workshop would yield an understanding of state-ofthe- art approaches for capturing and augmenting player satisfaction in interactive systems such as computer games. Our invited speaker was Hakon Steinø, Technical Producer of IO-Interactive, who discussed applied AI research at IO-Interactive, portrayed the future trends of AI in computer game industry and debated the use of academic-oriented methodologies for augmenting player satisfaction. The sessions of presentations and discussions where classified into three themes: Adaptive Learning, Examples of Adaptive Games and Player Modeling. The Workshop Committee did a great job in providing suggestions and informative reviews for the submissions; thank you! This workshop was in part supported by the Danish National Research Council (project no: 274-05-0511). Finally, thanks to all the participants; we hope you found this to be useful!peer-reviewe

Journey of Artificial Intelligence Frontier: A Comprehensive Overview

The field of Artificial Intelligence AI is a transformational force with limitless promise in the age of fast technological growth This paper sets out on a thorough tour through the frontiers of AI providing a detailed understanding of its complex environment Starting with a historical context followed by the development of AI seeing its beginnings and growth On this journey fundamental ideas are explored looking at things like Machine Learning Neural Networks and Natural Language Processing Taking center stage are ethical issues and societal repercussions emphasising the significance of responsible AI application This voyage comes to a close by looking ahead to AI s potential for human-AI collaboration ground-breaking discoveries and the difficult obstacles that lie ahead This provides with a well-informed view on AI s past present and the unexplored regions it promises to explore by thoroughly navigating this terrai

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research