How Will the Internet of Things Enable Augmented Personalized Health?

Sheth, Amit P.; Jaimini, Utkarshani; Yip, Hong Yung

doi:10.1109/mis.2018.012001556

Cited by 63 publications

(29 citation statements)

References 6 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Technological advancements over the last decade have transformed the health care system with a trend towards real-time monitoring, personal data analysis, and evidence-based diagnosis. Specifically, with the anticipated inclusion of individual's social data and the rapidly growing patient-generated health data [52], MHPs will be better informed about the patient's conditions including their suicidality to enable timely intervention.…”

Section: Figure 1: Changing Suicide Risk Of 3 Redditors Over a Periodmentioning

confidence: 99%

Knowledge-aware Assessment of Severity of Suicide Risk for Early Intervention

Gaur¹,

Alambo²,

Sain³

et al. 2019

The World Wide Web Conference

Self Cite

115

158

View full text Add to dashboard Cite

Mental health illness such as depression is a significant risk factor for suicide ideation, behaviors, and attempts. A report by Substance Abuse and Mental Health Services Administration (SAMHSA) shows that 80% of the patients suffering from Borderline Personality Disorder (BPD) have suicidal behavior, 5-10% of whom commit suicide. While multiple initiatives have been developed and implemented for suicide prevention, a key challenge has been the social stigma associated with mental disorders, which deters patients from seeking help or sharing their experiences directly with others including clinicians. This is particularly true for teenagers and younger adults where suicide is the second highest cause of death in the US. Prior research involving surveys and questionnaires (e.g. PHQ-9) for suicide risk prediction failed to provide a quantitative assessment of risk that informed timely clinical decision-making for intervention. Our interdisciplinary study concerns the use of Reddit as an unobtrusive data source for gleaning information about suicidal tendencies and other related mental health conditions afflicting depressed users. We provide details of our learning framework that incorporates domain-specific knowledge to predict the severity of suicide risk for an individual. Our approach involves developing a suicide risk severity lexicon using medical knowledge bases and suicide ontology to detect cues relevant to suicidal thoughts and actions. We also use language modeling, medical entity recognition and normalization and negation detection to create a dataset of 2181 redditors that have discussed or implied suicidal ideation, behavior, or attempt. Given the importance of clinical knowledge, our gold standard dataset of 500 redditors (out of 2181) was developed by four practicing psychiatrists following the guidelines outlined in This paper is published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license. Authors reserve their rights to disseminate the work on their personal and corporate Web sites with the appropriate attribution.

show abstract

Section: Figure 1: Changing Suicide Risk Of 3 Redditors Over a Periodmentioning

confidence: 99%

Knowledge-aware Assessment of Severity of Suicide Risk for Early Intervention

Gaur¹,

Alambo²,

Sain³

et al. 2019

The World Wide Web Conference

Self Cite

115

158

View full text Add to dashboard Cite

show abstract

“…In Figure 1, the conceptual model of the Internet of Things paradigm is illustrated. In [19], IoT is presented as a platform that provides information technology integration solutions that refer to the hardware and software used for storing, retrieving and processing biomedical data and communication technologies that include electronic systems used to communicate between individuals or groups, with the same pathologies.…”

Section: Literature Reviewmentioning

confidence: 99%

An Intelligent IoT-Based Food Quality Monitoring Approach Using Low-Cost Sensors

et al. 2019

View full text Add to dashboard Cite

The evolution of multipurpose sensors over the last decades has been investigated with the aim of developing innovative devices with applications in several fields of technology, including in the food industry. The integration of such sensors in food packaging technology has paved the way for intelligent food packaging. These integrated systems are capable of providing reliable information about the quality of the packed products during their storage period. To accomplish this goal, intelligent packs use a variety of sensors suited for monitoring the quality and safety of food products by recording the evolution of parameters like the quantity of pathogen agents, gases, temperature, humidity and storage period. This technology, when combined with IoT, is able to provide a lot more information than conventional food inspection technologies, which are limited to weight, volume, color and aspect inspection. The original system described in this work relies on a simple but effective method of integrated food monitoring, right at the client home, suitable for user prepared vacuum-packed foods. It builds upon the IoT concept and is able to create a network of interconnected devices. By using this approach, we are able to combine actuators and sensing devices also providing a common operating picture (COP) by sharing information over the platforms. More precisely, our system consists of gas, temperature and humidity sensors, which provide the essential information needed for evaluating the quality of the packed product. This information is transmitted wirelessly to a computer system providing an interface where the user can observe the evolution of the product quality over time.

show abstract

“…Algo relevante que permitirá Internet de las cosas será trascender la gestión intermitente y a corto plazo de algunos problemas de salud. En este contexto, será de gran valor contar con una recopilación longitudinal tanto de datos personalizados, como de datos medioambientales, algo útil para el seguimiento de los eventos de interés epidemiológico (27) . Por otro lado, el objetivo con los datos personalizados es lograr intervenciones más proactivas, muchas de las cuales estarán encaminadas a cambios en el estilo de vida, por consiguiente, el futuro de la salud individual y la salud pública dependerá, en buena medida, de cuánto se aprenda de estas estrategias que se convertirán en mejoras basadas en la evidencia (27) .…”

Section: Tecnología Al Servicio De La Salud La Epidemiología Y La Saunclassified

“…En este contexto, será de gran valor contar con una recopilación longitudinal tanto de datos personalizados, como de datos medioambientales, algo útil para el seguimiento de los eventos de interés epidemiológico (27) . Por otro lado, el objetivo con los datos personalizados es lograr intervenciones más proactivas, muchas de las cuales estarán encaminadas a cambios en el estilo de vida, por consiguiente, el futuro de la salud individual y la salud pública dependerá, en buena medida, de cuánto se aprenda de estas estrategias que se convertirán en mejoras basadas en la evidencia (27) . En este punto, la denominada Augmented Personalized Healthcare (APH) pretende potenciar el cuidado de la salud al sacar provecho de los datos personalizados obtenidos mediante Internet de las cosas con el uso de sensores, wearables, aplicaciones móviles, Electronic Medical Records (EMRs) y social media, utilizando técnicas de inteligencia artificial para mejorar la salud y el bienestar poblacional (28) .…”

Section: Tecnología Al Servicio De La Salud La Epidemiología Y La Saunclassified

Internet de las cosas: Futuro y desafío para la epidemiología y la salud pública

Rodríguez-Gómez

2019

Univ. Salud

View full text Add to dashboard Cite

Introducción: Internet vive una de las más grandes revoluciones de la historia denominada Internet de las cosas. En ella, tanto la epidemiología como la salud pública tienen gran potencial, ya que el nuevo mundo hiperconectado representará espacios de reinvención e innovación nunca antes imaginados en diversos aspectos del campo de la salud. Objetivo: Reflexionar sobre las posibilidades para la epidemiología y la salud pública ante el escenario de Internet de las cosas. Materiales y métodos: Revisión documental que incluyó textos físicos y bases de datos electrónicas. Resultados: Internet de las cosas representa para la epidemiología y la salud pública, una dimensión llena de oportunidades debido a las fuentes de datos masivos y a las tecnologías de la cuarta revolución industrial, aunque también nuevos desafíos, principalmente en cuanto a seguridad y privacidad de la información. Conclusiones: Ante la era de Internet de las cosas, para la salud en general y particularmente para la epidemiología y la salud pública, se abre la posibilidad múltiples fuentes de datos, muchas en tiempo real. Esto permitirá, optimizar la perspectiva y la comprensión de múltiples eventos en salud, y con ello, lograr una atención en salud más proactiva y predictiva.

show abstract

How Will the Internet of Things Enable Augmented Personalized Health?

Cited by 63 publications

References 6 publications

Knowledge-aware Assessment of Severity of Suicide Risk for Early Intervention

Knowledge-aware Assessment of Severity of Suicide Risk for Early Intervention

An Intelligent IoT-Based Food Quality Monitoring Approach Using Low-Cost Sensors

Internet de las cosas: Futuro y desafío para la epidemiología y la salud pública

Contact Info

Product

Resources

About