Processing of Electronic Health Records using Deep Learning: A review

Availability of large amount of clinical data is opening up new research avenues in a number of fields. An exciting field in this respect is healthcare, where secondary use of healthcare data is beginning to revolutionize healthcare. Except for availability of Big Data, both medical data from healthcare institutions (such as EMR data) and data generated from health and wellbeing devices (such as personal trackers), a significant contribution to this trend is also being made by recent advances on machine learning, specifically deep learning algorithms

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Quantum Readiness in Healthcare and Public Health: Building a Quantum Literate Workforce

Quantum technologies, including quantum computing, cryptography, and sensing, among others, are set to revolutionize sectors ranging from materials science to drug discovery. Despite their significant potential, the implications for public health have been largely overlooked, highlighting a critical gap in recognition and preparation. This oversight necessitates immediate action, as public health remains largely unaware of quantum technologies as a tool for advancement. The application of quantum principles to epidemiology and health informatics, termed quantum health epidemiology and quantum health informatics, has the potential to radically transform disease surveillance, prediction, modeling, and analysis of health data. However, there is a notable lack of quantum expertise within the public health workforce and educational pipelines. This gap underscores the urgent need for the development of quantum literacy among public health practitioners, leaders, and students to leverage emerging opportunities while addressing risks and ethical considerations. Innovative teaching methods, such as interactive simulations, games, visual models, and other tailored platforms, offer viable solutions for bridging knowledge gaps without the need for advanced physics or mathematics. However, the opportunity to adapt is fleeting as the quantum era in healthcare looms near. It is imperative that public health urgently focuses on updating its educational approaches, workforce strategies, data governance, and organizational culture to proactively meet the challenges of quantum disruption thereby becoming quantum ready.Comment: 13 pages, 1 tabl

Policy needs and options for a common approach towards modelling and simulation of human physiology and diseases with a focus on the virtual physiological human.

Life is the result of an intricate systemic interaction between many processes occurring at radically different spatial and temporal scales. Every day, worldwide biomedical research and clinical practice produce a huge amount of information on such processes. However, this information being highly fragmented, its integration is largely left to the human actors who find this task increasingly and ever more demanding in a context where the information available continues to increase exponentially. Investments in the Virtual Physiological Human (VPH) research are largely motivated by the need for integration in healthcare. As all health information becomes digital, the complexity of health care will continue to evolve, translating into an ever increasing pressure which will result from a growing demand in parallel to limited budgets. Hence, the best way to achieve the dream of personalised, preventive, and participative medicine at sustainable costs will be through the integration of all available data, information and knowledge

What Types of Predictive Analytics are Being Used in Talent Management Organizations?

[Excerpt] Talent management organizations are increasingly deriving insights from data to make better decisions. Their use of data analytics is advancing from descriptive to predictive and prescriptive analytics. Descriptive analytics is the most basic form, providing the hindsight view of what happened and laying the foundation for turning data into information. More advanced uses are predictive (advanced forecasts and the ability to model future results) and prescriptive (“the top-tier of analytics that leverage machine learning techniques … to both interpret data and recommend actions”) analytics (1). Appendix A illustrates these differences. This report summarizes our most relevant findings about how both academic researchers and HR practitioners are successfully using data analytics to inform decision-making in workforce issues, with a focus on executive assessment and selection

Anticipatory Mobile Computing: A Survey of the State of the Art and Research Challenges

Today's mobile phones are far from mere communication devices they were ten years ago. Equipped with sophisticated sensors and advanced computing hardware, phones can be used to infer users' location, activity, social setting and more. As devices become increasingly intelligent, their capabilities evolve beyond inferring context to predicting it, and then reasoning and acting upon the predicted context. This article provides an overview of the current state of the art in mobile sensing and context prediction paving the way for full-fledged anticipatory mobile computing. We present a survey of phenomena that mobile phones can infer and predict, and offer a description of machine learning techniques used for such predictions. We then discuss proactive decision making and decision delivery via the user-device feedback loop. Finally, we discuss the challenges and opportunities of anticipatory mobile computing.Comment: 29 pages, 5 figure

Modeling the impact of hospital logistics on quality of care and patient satisfaction: results of a survey in three public healthcare facilities in Fez - Morocco

Purpose: The objective of this research is to examine the role of hospital logistics in improving quality of care and patient satisfaction. Thus, the paper focuses on modeling and evaluating the relationship between these three constructs. Design/methodology/approach: In the present study, hospital logistics was specified as a second-order construct composed of five first-order constructs: physical accessibility, waiting time, consultation time, hospital hotel services, and administrative procedures. A questionnaire was developed and administered face-to-face to 384 hospitalized patients in three public healthcare facilities in Fez-Morocco. Collected data were processed and analyzed deploying the PLS-SEM method and using SmartPLS3 software. Data analysis was carried out by considering two types of patient circuits according to the admission modes in the healthcare facility: Urgent Patients Circuit and Scheduled Patients Circuit. Thus, two PLS-SEM models were evaluated and validated. Findings: Results highlighted the significant impact of hospital logistics on quality and satisfaction. In particular, the results of the two models showed that the most preponderant hospital logistics component is physical accessibility which consists of the availability and accessibility of ambulances, medical and nursing staff, support and guidance staff, technical facilities and equipment, etc. Thus, hospital managers and health system stakeholders should pay particular attention to hospital logistics activities in general and specifically to the physical accessibility to improve the quality of care and patient satisfaction. Research limitations/implications: This study only included patients from three public healthcare facilities in Fez-Morocco. Also, the model variables of hospital logistics construct are restricted and were applied in a specific context. Besides, the sample size was relatively reduced. Thus, results generalization might be limited. Further studies including more patients from other territories and including other logistics components are needed for large-scale validation of the proposed model. Originality/value: The results of this study contribute to the scientific literature on hospital logistics and its role as a lever for quality of care and patient satisfaction.Peer Reviewe

Mining User-generated Content of Mobile Patient Portal: Dimensions of User Experience

Patient portals are positioned as a central component of patient engagement through the potential to change the physician-patient relationship and enable chronic disease self-management. The incorporation of patient portals provides the promise to deliver excellent quality, at optimized costs, while improving the health of the population. This study extends the existing literature by extracting dimensions related to the Mobile Patient Portal Use. We use a topic modeling approach to systematically analyze users’ feedback from the actual use of a common mobile patient portal, Epic\u27s MyChart. Comparing results of Latent Dirichlet Allocation analysis with those of human analysis validated the extracted topics. Practically, the results provide insights into adopting mobile patient portals, revealing opportunities for improvement and to enhance the design of current basic portals. Theoretically, the findings inform the social-technical systems and Task-Technology Fit theories in the healthcare field and emphasize important healthcare structural and social aspects. Further, findings inform the humanization of healthcare framework, support the results of existing studies, and introduce new important design dimensions (i.e., aspects) that influence patient satisfaction and adherence to patient portal