Towards developing an intelligent agent to assist in patient diagnosis using neural networks on unstructured patient clinical notes: Initial analysis and models

Technological advances in information-communication technologies in the health ecosystem have allowed for the recording and consumption of massive amounts of structured and unstructured health data. In developing countries, the use of Electronic Medical Records (EMR) is necessary to address the need for efficient delivery of services and informed decision-making, especially at the local level where health facilities and practitioners may be lacking. Text mining is a variation of data mining that tries to extract non-trivial information and knowledge from unstructured text. This study aims to determine the feasibility of integrating an intelligent agent within EMRs for automatic diagnosis prediction based on the unstructured clinical notes. A Multilayer Feed- Forward Neural Network with Back Propagation training was implemented for classification. The two neural network models predicted hypertension against similar diagnoses with 11.52% and 10.53% percent errors but predicted with 54.01% and 64.82% percent errors when used on a group of similar diagnoses. Further development is needed for prediction of diagnoses with common symptoms and related diagnoses. The results still prove, however, that unstructured data possesses value beneficial for clinical decision support. If further analyzed with structured data, a more accurate intelligent agent may be explored

Investigating the use of real-time data in nudging patients' Emergency Department (ED) attendance behaviour

This is the author accepted manuscript. The final version is available from the Society for Modeling and Simulation International via the URL in this record.Decision-making in healthcare is a complex process involving multiple stakeholders. One such stakeholder category is the intended users of the system itself – the patients. We present a study in which users use real-time hospital operations data to make attendance choices. The work was carried out with the Torbay & South Devon NHS Foundation Trust (TSDFT) and its network of Minor Injury Units (MIUs) and one Emergency Department (ED). The aim of this research was to provide information transparency on ED/MIU waiting times which would allow recipients, including, significantly, patients who are in need of urgent medical attention, to make informed decisions as to the facility that could best serve their needs. This work will contribute towards reducing pressure in ED by redistributing demand for minor ailments among the MIUs, since the MIUs have facilities for the treatment of minor injuries and the ED exists mainly for emergency and life-threating conditions.We would like to acknowledge the ESRC Impact Acceleration Account on Project Co-creation for the project on “Systems Modelling and Computer Simulation of Urgent and Emergency Care in Torbay & South Devon"

Block-Chain-Based Vaccine Volunteer Records Secure Storage and Service Structure

Accurate and complete vaccine volunteer’s data are one valuable asset for clinical research institutions. Privacy protection and the safe storage of vaccine volunteer’s data are vital concerns during clinical trial services. The advent of block-chain technology fetches an innovative idea to solve this problem. As a hash chain with the features of decentralization, authentication, and resistibility, blockchain-based technology can be used to safely store vaccine volunteer clinical trial data. In this paper, we proposed a safe storage method to control volunteer personal /clinical trial data based on blockchain with storing on cloud. Also, a service structure for sharing data of volunteer’s vaccine clinical trials is defined. Further, volunteer blockchain features are defined and examined. The projected storage and distribution method is independent of any third person and no single person has the complete influence to disturb the processing.

A privacy-preserving data storage and service framework based on deep learning and blockchain for construction workers' wearable IoT sensors

Classifying brain signals collected by wearable Internet of Things (IoT) sensors, especially brain-computer interfaces (BCIs), is one of the fastest-growing areas of research. However, research has mostly ignored the secure storage and privacy protection issues of collected personal neurophysiological data. Therefore, in this article, we try to bridge this gap and propose a secure privacy-preserving protocol for implementing BCI applications. We first transformed brain signals into images and used generative adversarial network to generate synthetic signals to protect data privacy. Subsequently, we applied the paradigm of transfer learning for signal classification. The proposed method was evaluated by a case study and results indicate that real electroencephalogram data augmented with artificially generated samples provide superior classification performance. In addition, we proposed a blockchain-based scheme and developed a prototype on Ethereum, which aims to make storing, querying and sharing personal neurophysiological data and analysis reports secure and privacy-aware. The rights of three main transaction bodies - construction workers, BCI service providers and project managers - are described and the advantages of the proposed system are discussed. We believe this paper provides a well-rounded solution to safeguard private data against cyber-attacks, level the playing field for BCI application developers, and to the end improve professional well-being in the industry

Research and Discovery Science and the Future of Dental Education and Practice

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153692/1/jddjde017040.pd

Analysis of an Internet Community about Pneumothorax and the Importance of Accurate Information about the Disease.

Background: The huge improvements in the speed of data transmission and the increasing amount of data available as the Internet has expanded have made it easy to obtain information about any disease. Since pneumothorax frequently occurs in young adolescents, patients often search the Internet for information on pneumothorax. Methods: This study analyzed an Internet community for exchanging information on pneumothorax, with an emphasis on the importance of accurate information and doctors' role in providing such information. Results: This study assessed 599,178 visitors to the Internet community from June 2008 to April 2017. There was an average of 190 visitors, 2.2 posts, and 4.5 replies per day. A total of 6,513 posts were made, and 63.3% of them included questions about the disease. The visitors mostly searched for terms such as 'pneumothorax,' 'recurrent pneumothorax,' 'pneumothorax operation,' and 'obtaining a medical certification of having been diagnosed with pneumothorax.' However, 22% of the pneumothorax-related posts by visitors contained inaccurate information. Conclusion: Internet communities can be an important source of information. However, incorrect information about a disease can be harmful for patients. We, as doctors, should try to provide more in-depth information about diseases to patients and to disseminate accurate information about diseases in Internet communities.ope

Development of a web software prototype to support retirement planning

Objetivo desarrollar un prototipo de web software de apoyo a la planificación de la jubilación. Método se trata de una investigación metodológica, aplicada, pautada en los principios del modelo prototipado, que siguió las etapas de comunicación, planificación, creación del prototipo, pruebas de funcionamiento y consolidación de la versión 1 del web software . Resultados las funciones del prototipo del web software se definieron a partir de un diagrama de flujo y del ámbito. En la etapa de creación fueron proyectadas las pantallas que integraron el prototipo, compuesto por entrevista, completando el Inventario de Recursos para la Jubilación, pantalla de acceso a materiales de apoyo a la planificación, incluyendo conferencias, textos científicos y materiales técnicos; pantalla de noticias sobre la jubilación, pantalla de vivencias, las cuales permiten a los usuarios publicar expectativas en relación a la jubilación y comentar publicaciones de otros usuarios. Después de la realización de las pruebas de funcionamiento, el prototipo estuvo disponible en la dirección www.aposentarsecomsaude.com.br. Conclusión el prototipo del web software consiste en un ambiente interactivo, en el cual el usuario se siente activo en el proceso de reflexión sobre la jubilación a lo largo de las diferentes pantallas. Con lenguaje y expresiones claras, de fácil entendimiento al público distinto al que se destinan, se vuelve aplicable a los usuarios de diferentes perfiles profesionales.Objetivo desenvolver um protótipo de web software de apoio ao planejamento da aposentadoria. Método trata-se de uma pesquisa metodológica, aplicada, pautada nos princípios do modelo de prototipação, que seguiu as etapas de comunicação, planejamento, criação do protótipo, testes de funcionamento e consolidação da versão 1 do web software . Resultados as funções do protótipo do web software foram definidas a partir de um fluxograma e do escopo. Na etapa de criação foram projetadas as telas que integraram o protótipo, composto por entrevista, a partir do preenchimento do Inventário de Recursos para a Aposentadoria, tela de acesso aos materiais de apoio ao planejamento, incluindo palestras, textos científicos e materiais técnicos, tela de notícias sobre a aposentadoria, tela de vivências, as quais permitem aos usuários publicar expectativas em relação à aposentadoria e comentar publicações de outros usuários. Após a realização dos testes de funcionamento, o protótipo foi disponibilizado no endereço www.aposentarsecomsaude.com.br. Conclusão o protótipo do web software consiste em um ambiente interativo, no qual o usuário sente-se ativo no processo de reflexão sobre a aposentadoria ao longo das diferentes telas. Com linguagem e expressões claras, de fácil entendimento ao público distinto a que se destina, torna-se aplicável aos usuários de diferentes perfis profissionais.Objective To develop a web software prototype to support retirement planning. Method This is a methodological research, applied and based on the principles of prototyping model, which followed the steps of communication, planning, prototype creation, functional tests and consolidation of web software version 1. Results The functions of the web software prototype were defined from a flowchart and scope. In the creation stage, the screens that integrated the prototype, composed by interview, were projected from the filling of the Retirement Resources Inventory, screen of access to support planning materials, including lectures, scientific texts, and technical materials, retirement news screen, experiences screen, which allow users to post retirement expectations and comment on other users’ posts. After performing tests, the prototype was made available at www.aposentarsecomsaude.com.br . Conclusion the web software prototype consists of an interactive environment in which the user feels active in the reflection process about the retirement along the different screens. With clear language and expressions that are easily understood by the public, they are applicable to users of different professional profiles

e-Visits For Early Post-operative Visits Following Orthopaedic Surgery Can They Add Efficiency Without Sacrificing Effectiveness

We asked 217 sport surgery and 135 total knee arthroplasty (TKA) patients to complete a questionnaire (e-Visit) before attending their two and six-week post-operative appointment. Our primary objective was to use the questions asked of patients prior to their appointment to develop a model that could be used as web-based e-Visit to predict early post-operative adverse events. Gold standard comparison was the surgeon’s opinion as to the presence or absence of an event at follow-up. Secondary objective was evaluation of a simplified model. We found good area under the curve (AUC) statistics (0.76 (95% CI 0.69 - 0.84) and 0.80 (95% CI .74 - .85)) and good sensitivity (0.70, 0.83) and specificity (0.70, 0.80) for the two- week model and for the six-week model respectively. The simplified models and raw-data models were similar. Future work should improve the web-based interface, include educational content, and be validated using a large multicenter RCT

Analysis and Visualization Methods for Data-Driven Longitudinal Patient Summary

Digitization of health records has opened avenues for intensive research in the fields of health informatics. Power of machine learning, statistical analysis and visual analytics could be utilized to make optimal use of this information. The proposed project is to develop an interactive visualization tool that summarizes a patient's medical history, highlighting all his/her important events based on the knowledge of similar patients. Given a set of patients with common conditions, statistical analysis can be used to develop models that prioritize features based on associations between features and condition-specific outcome measures. This manuscript in particular describes the model developed to prioritize a patient's events from his medical history. The model is trained with the population of patients and their events. Their correlations with the outcome variable are calculated to identify the important events in a specific cohort. This correlation score can be used to prioritize the events associated with an individual patient. This model is one of the models that will be used to summarize an individual patient's medical data via interactive visualization methods.Master of Science in Information Scienc