Sequential anomaly detection in the presence of noise and limited feedback

This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: 1) filtering, or assigning a belief or likelihood to each successive measurement based upon our ability to predict it from previous noisy observations and 2) hedging, or flagging potential anomalies by comparing the current belief against a time-varying and data-adaptive threshold. The threshold is adjusted based on the available feedback from an end user. Our algorithms, which combine universal prediction with recent work on online convex programming, do not require computing posterior distributions given all current observations and involve simple primal-dual parameter updates. At the heart of the proposed approach lie exponential-family models which can be used in a wide variety of contexts and applications, and which yield methods that achieve sublinear per-round regret against both static and slowly varying product distributions with marginals drawn from the same exponential family. Moreover, the regret against static distributions coincides with the minimax value of the corresponding online strongly convex game. We also prove bounds on the number of mistakes made during the hedging step relative to the best offline choice of the threshold with access to all estimated beliefs and feedback signals. We validate the theory on synthetic data drawn from a time-varying distribution over binary vectors of high dimensionality, as well as on the Enron email dataset. © 1963-2012 IEEE.

Toward the development of national telehealth services: the role of Veterans Health Administration and future directions for research.

The Veterans Health Administration (VHA) in the Department of Veteran Affairs (VA) has emerged as a national and international leader in the delivery and research of telehealth-based treatment. Several unique characteristics of care in VA settings intersect to create an ideal environment for telehealth modalities and research. However, the value of telehealth experience and initiatives in VA settings is limited if telehealth strategies cannot be widely exported to other public or private systems. Whereas a hierarchical organization, such as VA, can innovate and fund change relatively quickly based on provider and patient preferences and a growing knowledge base, other health provider organizations and third-party payers may likely require replicable scientific findings over time before incremental investments will be made to create infrastructure, reform regulatory barriers, and amend laws to accommodate expansion of telehealth modalities. Accordingly, large-scale scientifically rigorous telehealth research in VHA settings is essential not only to investigate the efficacy of existing and future telehealth practices in VHA, but also to hasten the development of telehealth infrastructure in private and other public health settings. We propose an expanded partnership between the VA, NIH, and other funding agencies to investigate creative and pragmatic uses of telehealth technology. To this end, we identify six specific areas of research we believe to be particularly relevant to the efficient development of telehealth modalities in civilian and military contexts outside VHA.

Reference groups and product line decisions: An experimental investigation of limited editions and product proliferation

Some luxury goods manufacturers offer limited editions of their products, whereas some others market multiple product lines. Researchers have found that reference groups shape consumer evaluations of these product categories. Yet little empirical research has examined how reference groups affect the product line decisions of firms. Indeed, in a field setting it is quite a challenge to isolate reference group effects from contextual effects and correlated effects. In this paper, we propose a parsimonious model that allows us to study how reference groups influence firm behavior and that lends itself to experimental analysis. With the aid of the model we investigate the behavior of consumers in a laboratory setting where we can focus on the reference group effects after controlling for the contextual and correlated effects. The experimental results show that in the presence of strong reference group effects, limited editions and multiple products can help improve firms' profits. Furthermore, the trends in the purchase decisions of our participants point to the possibility that they are capable of introspecting close to two steps of thinking at the outset of the game and then learning through reinforcement mechanisms. © 2010 INFORMS.

Towards a field-compatible optical spectroscopic device for cervical cancer screening in resource-limited settings: effects of calibration and pressure.

Quantitative optical spectroscopy has the potential to provide an effective low cost, and portable solution for cervical pre-cancer screening in resource-limited communities. However, clinical studies to validate the use of this technology in resource-limited settings require low power consumption and good quality control that is minimally influenced by the operator or variable environmental conditions in the field. The goal of this study was to evaluate the effects of two sources of potential error: calibration and pressure on the extraction of absorption and scattering properties of normal cervical tissues in a resource-limited setting in Leogane, Haiti. Our results show that self-calibrated measurements improved scattering measurements through real-time correction of system drift, in addition to minimizing the time required for post-calibration. Variations in pressure (tested without the potential confounding effects of calibration error) caused local changes in vasculature and scatterer density that significantly impacted the tissue absorption and scattering properties Future spectroscopic systems intended for clinical use, particularly where operator training is not viable and environmental conditions unpredictable, should incorporate a real-time self-calibration channel and collect diffuse reflectance spectra at a consistent pressure to maximize data integrity.

Ethics Standards (HRPP) and Public Partnership (PARTAKE) to Address Clinical Research Concerns in India: Moving Toward Ethical, Responsible, Culturally Sensitive, and Community-Engaging Clinical Research.

Like other emerging economies, India's quest for independent, evidence-based, and affordable healthcare has led to robust and promising growth in the clinical research sector, with a compound annual growth rate (CAGR) of 20.4% between 2005 and 2010. However, while the fundamental drivers and strengths are still strong, the past few years witnessed a declining trend (CAGR -16.7%) amid regulatory concerns, activist protests, and sponsor departure. And although India accounts for 17.5% of the world's population, it currently conducts only 1% of clinical trials. Indian and international experts and public stakeholders gathered for a 2-day conference in June 2013 in New Delhi to discuss the challenges facing clinical research in India and to explore solutions. The main themes discussed were ethical standards, regulatory oversight, and partnerships with public stakeholders. The meeting was a collaboration of AAHRPP (Association for the Accreditation of Human Research Protection Programs)-aimed at establishing responsible and ethical clinical research standards-and PARTAKE (Public Awareness of Research for Therapeutic Advancements through Knowledge and Empowerment)-aimed at informing and engaging the public in clinical research. The present article covers recent clinical research developments in India as well as associated expectations, challenges, and suggestions for future directions. AAHRPP and PARTAKE provide etiologically based solutions to protect, inform, and engage the public and medical research sponsors.