Integration of BI in Healthcare

2020 ◽  
pp. 166-184
Author(s):  
Xue Ning
Keyword(s):  
Decision Making ◽  
Health Data ◽  
Medical Data ◽  
Unstructured Data ◽  
Clinical Text ◽  
Complex Process ◽  
Types Of Information ◽  
Media Data ◽  
Support Decision Making ◽  
Tools And Methods

In the digital age, the healthcare industry is generating a huge amount of data and information. Although there are structured data such as EHRs, the major data type is unstructured data such as clinical text. The sources of health data are also diversified, including medical data, clinical data, patient-generated data, and social media data. Different methods are applied to analyze the variety of data and obtain health information. When the various types of information are generated, information retrieval and extraction techniques can be used for further decision-making. Data and information-enabled decision-making is a complex process. Many tools and methods are developed to support decision-making in healthcare. Along with the benefits of integrating business intelligence in healthcare, issues and challenges exist. This chapter discusses the health data and information and how they support decision-making in healthcare.

Integration of BI in Healthcare

2021 ◽  
pp. 969-982
Author(s):  
Xue Ning
Keyword(s):  
Decision Making ◽  
Health Data ◽  
Medical Data ◽  
Unstructured Data ◽  
Clinical Text ◽  
Complex Process ◽  
Types Of Information ◽  
Media Data ◽  
Support Decision Making ◽  
Tools And Methods

In the digital age, the healthcare industry is generating a huge amount of data and information. Although there are structured data such as EHRs, the major data type is unstructured data such as clinical text. The sources of health data are also diversified, including medical data, clinical data, patient-generated data, and social media data. Different methods are applied to analyze the variety of data and obtain health information. When the various types of information are generated, information retrieval and extraction techniques can be used for further decision-making. Data and information-enabled decision-making is a complex process. Many tools and methods are developed to support decision-making in healthcare. Along with the benefits of integrating business intelligence in healthcare, issues and challenges exist. This chapter discusses the health data and information and how they support decision-making in healthcare.

IMPLEMENTASI METODE VIKOR DALAM PENERIMAAN JURNALIS PADA KORAN WASPADA MEDAN

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Soraya Rahma Hayati ◽  
Mesran Mesran ◽  
Taronisokhi Zebua ◽  
Heri Nurdiyanto ◽  
Khasanah Khasanah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Knowledge Based ◽  
Computer Based ◽  
Support Decision Making ◽  
Made In

The reception of journalists at the Waspada Daily Medan always went through several rigorous selections before being determined to be accepted as journalists at the Waspada Medan Daily. There are several criteria that must be possessed by each participant as a condition for becoming a journalist in the Daily Alert Medan. To get the best participants, the Waspada Medan Daily needed a decision support system. Decision Support Systems (SPK) are part of computer-based information systems (including knowledge-based systems (knowledge management)) that are used to support decision making within an organization or company. Decision support systems provide a semitructured decision, where no one knows exactly how the decision should be made. In this study the authors applied the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the method to be applied in the decision support system application. The VIKOR method is part of the Multi-Attibut Decision Making (MADM) Concept, which requires normalization in its calculations. The expected results in this study can obtain maximum decisions.Keywords: Journalist Acceptance, Decision Support System, VIKOR

Doping in sports – conscious lack of interest or ethical Everest?

2017 ◽  
Vol 65 (4) ◽  
Keyword(s):  
Decision Making ◽  
General Population ◽  
Medical Setting ◽  
Doping In Sports ◽  
Physician Relationship ◽  
Pharmaceutical Agents ◽  
Similar Development ◽  
Level Performance ◽  
Elite Sports ◽  
Support Decision Making

Within a clinical sports medical setting the discussion about doping is insufficient. In elite-sports use of pharmaceutical agents is daily business in order to maintain the expected top-level performance. Unfortunately, a similar development could be observed in the general population of leisure athletes where medical supervision is absent. As a sports physician you are facing imminent ethical questions when standing in between. Therefore, we propose the application of a standardised risk score as a tool to promote doping-prevention and launch the debate within athlete-physician-relationship. In the longterm such kind of risk stratification systems may support decision-making with regard to «protective» exclusion of sporting competition.

scholarly journals Explaining deep neural networks for knowledge discovery in electrocardiogram analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Steven A. Hicks ◽  
Jonas L. Isaksen ◽  
Vajira Thambawita ◽  
Jonas Ghouse ◽  
Gustav Ahlberg ◽  
...  
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Deep Neural Networks ◽  
Clinical Decision Making ◽  
Medical Knowledge ◽  
Clinical Decision ◽  
Medical Data ◽  
Medical Doctors ◽  
Medical Tests ◽  
Deep Learning Model

AbstractDeep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction should be accompanied by an explanation that a human can understand. We present an approach called electrocardiogram gradient class activation map (ECGradCAM), which is used to generate attention maps and explain the reasoning behind deep learning-based decision-making in ECG analysis. Attention maps may be used in the clinic to aid diagnosis, discover new medical knowledge, and identify novel features and characteristics of medical tests. In this paper, we showcase how ECGradCAM attention maps can unmask how a novel deep learning model measures both amplitudes and intervals in 12-lead electrocardiograms, and we show an example of how attention maps may be used to develop novel ECG features.

scholarly journals Individual differences in experienced and observational decision-making illuminate interactions between reinforcement learning and declarative memory

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Batel Yifrah ◽  
Ayelet Ramaty ◽  
Genela Morris ◽  
Avi Mendelsohn
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Declarative Memory ◽  
Contextual Information ◽  
Memory Performance ◽  
Relevant Information ◽  
Subjective Memory ◽  
Types Of Information ◽  
Reinforcement Learning Models ◽  
Implicit And Explicit

AbstractDecision making can be shaped both by trial-and-error experiences and by memory of unique contextual information. Moreover, these types of information can be acquired either by means of active experience or by observing others behave in similar situations. The interactions between reinforcement learning parameters that inform decision updating and memory formation of declarative information in experienced and observational learning settings are, however, unknown. In the current study, participants took part in a probabilistic decision-making task involving situations that either yielded similar outcomes to those of an observed player or opposed them. By fitting alternative reinforcement learning models to each subject, we discerned participants who learned similarly from experience and observation from those who assigned different weights to learning signals from these two sources. Participants who assigned different weights to their own experience versus those of others displayed enhanced memory performance as well as subjective memory strength for episodes involving significant reward prospects. Conversely, memory performance of participants who did not prioritize their own experience over others did not seem to be influenced by reinforcement learning parameters. These findings demonstrate that interactions between implicit and explicit learning systems depend on the means by which individuals weigh relevant information conveyed via experience and observation.

A multi-layered disassembly sequence planning method to support decision making in de-manufacturing

Sadhana ◽  
2021 ◽  
Vol 46 (2) ◽  
Author(s):  
Gulivindala Anil Kumar ◽  
M V A Raju Bahubalendruni ◽  
V S S Prasad ◽  
K Sankaranarayanasamy
Keyword(s):  
Decision Making ◽  
Planning Method ◽  
Disassembly Sequence Planning ◽  
Sequence Planning ◽  
Disassembly Sequence ◽  
Support Decision Making

scholarly journals Public Officials’ Knowledge of Advances and Gaps for Implementing the Ecosystem Approach to Fisheries in Chile

2021 ◽  
Vol 13 (5) ◽  
pp. 2703
Author(s):  
Rodrigo A. Estévez ◽  
Stefan Gelcich
Keyword(s):  
Decision Making ◽  
Fisheries Management ◽  
Cost Effective ◽  
Ecosystem Approach ◽  
Social Dimensions ◽  
Public Officials ◽  
Government Officials ◽  
Effective Implementation ◽  
Mandatory Requirement ◽  
Support Decision Making

The United Nations calls on the international community to implement an ecosystem approach to fisheries (EAF) that considers the complex interrelationships between fisheries and marine and coastal ecosystems, including social and economic dimensions. However, countries experience significant national challenges for the application of the EAF. In this article, we used public officials’ knowledge to understand advances, gaps, and priorities for the implementation of the EAF in Chile. For this, we relied on the valuable information held by fisheries managers and government officials to support decision-making. In Chile, the EAF was established as a mandatory requirement for fisheries management in 2013. Key positive aspects include the promotion of fishers’ participation in inter-sectorial Management Committees to administrate fisheries and the regulation of bycatch and trawling on seamounts. Likewise, Scientific Committees formal roles in management allow the participation of scientists by setting catch limits for each fishery. However, important gaps were also identified. Officials highlighted serious difficulties to integrate social dimensions in fisheries management, and low effective coordination among the institutions to implement the EAF. We concluded that establishing clear protocols to systematize and generate formal instances to build upon government officials’ knowledge seems a clear and cost effective way to advance in the effective implementation of the EAF.

Comparing Two Decision Support Modes Using the Cognitive Shadow Online Policy-Capturing System

2020 ◽  
Vol 64 (1) ◽  
pp. 1125-1129
Author(s):  
Katherine Labonté ◽  
Daniel Lafond ◽  
Aren Hunter ◽  
Heather F. Neyedli ◽  
Sébastien Tremblay
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Response Pattern ◽  
Policy Capturing ◽  
Model Accuracy ◽  
Prototype Tool ◽  
Human Operators ◽  
Support Decision Making ◽  
Threat Evaluation

The Cognitive Shadow is a prototype tool intended to support decision making by autonomously modeling human operators’ response pattern and providing online notifications to the operators about the decision they are expected to make in new situations. Since the system can be configured either in a reactive “shadowing” or a proactive “recommendation” mode, this study aimed to determine its most effective mode in terms of human and model accuracy, workload, and trust. Subjects participated in an aircraft threat evaluation simulation without decision support or while using either mode of the Cognitive Shadow. Whereas the recommendation mode had no advantage over the control condition, the shadowing mode led to higher human and model accuracy. These benefits were maintained even when the tool was unexpectedly removed. Neither mode influenced workload, and the initial lower trust rating in the shadowing mode faded quickly, making it the best overall configuration for the cognitive assistant.

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