Using Big Data for Clinical Decision Making
نویسندگان
چکیده
منابع مشابه
Benchmark Forecasting in Data Envelopment Analysis for Decision Making Units
Although DEA is a powerful method in evaluating DMUs, it does have some limitations. One of the limitations of this method is the result of the evaluation is based on previously data and the results are not proper for forecasting the future changes. So For this purpose, we design feedback loops for forecasting inputs and outputs through system dynamics and simulation. Then we use DEA model to f...
متن کاملData mining for decision making in engineering optimal design
Often in modeling the engineering optimization design problems, the value of objective function(s) is not clearly defined in terms of design variables. Instead it is obtained by some numerical analysis such as FE structural analysis, fluid mechanic analysis, and thermodynamic analysis, etc. Yet, the numerical analyses are considerably time consuming to obtain the final value of objective functi...
متن کاملUsing Big Data Classification and Mining for the Decision-making 2.0 Process
Web 2.0 is a revolution that has affected all areas, especially those of the new technology. Several new concepts have emerged, and a large number of innovative applications continue to come out every day. However, the social networking remains the racehorse of web 2.0, giving the user at the same time, a space for communication and for information sharing, which generates too much data, variab...
متن کاملTemporal Horizons and Decision-Making: A Big Data Approach
Human behavior is plagued by shortsightedness. When faced with two options, smaller rewards are often chosen over larger rewards, even when such choices are potentially costly. In three experiments, we use big data techniques to examine how such choices might be driven by people’s temporal horizons. In Experiment 1, we determine the average distance into the future people talk about in their tw...
متن کاملDecision support using Bayesian networks for clinical decision making
This thesis investigates the use of Bayesian Networks (BNs), augmented by the Dynamic Discretization Algorithm, to model a variety of clinical problems. In particular, the thesis demonstrates four novel applications of BN and dynamic discretization to clinical problems. Firstly, it demonstrates the flexibility of the Dynamic Discretization Algorithm in modeling existing medical knowledge using ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Innovation in Aging
سال: 2020
ISSN: 2399-5300
DOI: 10.1093/geroni/igaa057.563