Machine learning-based consensus decision-making support for crowd-scale deliberation

2021 ◽  
Author(s):  
Chunsheng Yang ◽  
Wen Gu ◽  
Takayuki Ito ◽  
Xiaohua Yang
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Consensus Decision Making ◽  
Consensus Decision ◽  
Decision Making Support

scholarly journals Consensus Decision Making by Fish

2008 ◽  
Vol 18 (22) ◽  
pp. 1773-1777 ◽  
Author(s):  
David J.T. Sumpter ◽  
Jens Krause ◽  
Richard James ◽  
Iain D. Couzin ◽  
Ashley J.W. Ward
Keyword(s):  
Decision Making ◽  
Consensus Decision Making ◽  
Consensus Decision

scholarly journals Real-Time AI-Based Informational Decision-Making Support System Utilizing Dynamic Text Sources

2021 ◽  
Vol 11 (13) ◽  
pp. 6237
Author(s):  
Azharul Islam ◽  
KyungHi Chang
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Random Forest ◽  
Support System ◽  
Classification Accuracy ◽  
Short Term Memory ◽  
Learning Algorithm ◽  
Unstructured Data ◽  
Stochastic Gradient Descent ◽  
Decision Making Support

Unstructured data from the internet constitute large sources of information, which need to be formatted in a user-friendly way. This research develops a model that classifies unstructured data from data mining into labeled data, and builds an informational and decision-making support system (DMSS). We often have assortments of information collected by mining data from various sources, where the key challenge is to extract valuable information. We observe substantial classification accuracy enhancement for our datasets with both machine learning and deep learning algorithms. The highest classification accuracy (99% in training, 96% in testing) was achieved from a Covid corpus which is processed by using a long short-term memory (LSTM). Furthermore, we conducted tests on large datasets relevant to the Disaster corpus, with an LSTM classification accuracy of 98%. In addition, random forest (RF), a machine learning algorithm, provides a reasonable 84% accuracy. This research’s main objective is to increase the application’s robustness by integrating intelligence into the developed DMSS, which provides insight into the user’s intent, despite dealing with a noisy dataset. Our designed model selects the random forest and stochastic gradient descent (SGD) algorithms’ F1 score, where the RF method outperforms by improving accuracy by 2% (to 83% from 81%) compared with a conventional method.

scholarly journals PERAN PERAWAT DALAM MENGANALISIS BUDAYA ORGANISASI DAN BUDAYA KESELAMATAN PASIEN DI RUMAH SAKIT

2019 ◽  
Author(s):  
Muhaini Atmayana Purba
Keyword(s):  
Decision Making ◽  
Consensus Decision Making ◽  
Consensus Decision

Latar belakang : Membangun budaya keselamatan pasien merupakan langkah awal dalam pengembangan keselamatan pasien. Budaya keselamatan pasien di rumah sakit merupakan bagian dari budaya organisasi, sehingga pengkajian tentang budaya organisasi diperlukan untuk menjadi panduan dalam mengembangkan keselamatan pasien. Tujuan : Tujuan penulisan ini yaitu mengidenifikasi peran perawat dalam menganalisis budaya organisasi dan budaya keselamatan pasien di rumah sakit. Metode : Metode yang digunakan merupakan literatur review atau suatu perbandingan atau analisis antara satu jurnal dengan jurnal lainnya dari berbagai sumber seperti referensi jurnal, buku teks dan e-book. Hasil : Tipe budaya Clan didapatkan sebagai tipe budaya organisasi yang dominan sekaligus kuat dan menjadi panduan untuk melakukan perubahan dalam organisasi khususnya dalam pengembangan keselamatan pasien. Rencana tindak lanjut dibuat dan disepakati dalam Consensus Decision Making Group (CDMG) untuk mengartikulasikan unsur keselamatan pasien dalam visi dan misi organisasi serta penguatan budaya keselamatan melalui pelatihan keselamatan pasien bagi seluruh staf. Kesimpulan : . Rencana dalam tindak lanjut dibuat dan disepakati dalam Consensus Decision Making Group (CDMG) untuk mengartikulasikan unsur keselamatan pasien dalam visi dan misi organisasi serta penguatan budaya keselamatan melalui pelatihan keselamatan pasien bagi seluruh staf dan juga perawat.

scholarly journals Communication speeds up but impairs the consensus decision in a dyadic colour estimation task

2020 ◽  
Vol 7 (7) ◽  
pp. 191974
Author(s):  
Liutao Yu ◽  
Chundi Wang ◽  
Si Wu ◽  
Da-Hui Wang
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Daily Life ◽  
Consensus Formation ◽  
Exact Role ◽  
Estimation Task ◽  
Consensus Decision Making ◽  
Consensus Decision ◽  
Better Than

Communication plays an important role in consensus decision-making which pervades our daily life. However, the exact role of communication in consensus formation is not clear. Here, to study the effects of communication on consensus formation, we designed a dyadic colour estimation task, where a pair of isolated participants repeatedly estimated the colours of discs until they reached a consensus or completed eight estimations, either with or without communication. We show that participants’ estimates gradually approach each other, reaching towards a consensus, and these are enhanced with communication. We also show that dyadic consensus estimation is on average better than individual estimation. Surprisingly, consensus estimation without communication generally outperforms that with communication, indicating that communication impairs the improvement of consensus estimation. However, without communication, it takes longer to reach a consensus. Moreover, participants who partially cooperate with each other tend to result in better overall consensus. Taken together, we have identified the effect of communication on the dynamics of consensus formation, and the results may have implications on group decision-making in general.

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