Back

A Data-Driven Evaluation Approach for Assessing Student Nurse Training Effectiveness in Clinical Practice Using A Fuzzy Mathematics Model

Liu, Y.; Chen, Y.

2020-09-29 nursing
10.1101/2020.09.28.20203570 medRxiv
Show abstract

The overall performance of student nurses during training and subsequent medical treatment practice has a direct effect on the quality of healthcare they provide in hospitals. The evaluation of student nurses overall performance is usually not straightforward, as the evaluation criteria includes many aspects and its difficult to develop a generic metric. Fuzzy mathematics provides a mathematical tool for processing data with fuzziness. Using fuzzy mathematics theory enables data-driven evaluation of the overall performance of student nurses after their training program.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

1
PLOS ONE
● 5266 papers in training set
Top 0.5%
55.9%
Similar papers in this journal
50% of probability mass above
2
Frontiers in Public Health
○ 148 papers in training set
Top 0.5%
6.5%
Similar papers in this journal
3
International Journal of Environmental Research and Public Health
○ 128 papers in training set
Top 1%
4.2%
Similar papers in this journal
4
Frontiers in Medicine
○ 120 papers in training set
Top 0.6%
4.2%
Similar papers in this journal
5
Sensors
○ 43 papers in training set
Top 0.4%
2.5%
Similar papers in this journal
6
Medicine
○ 31 papers in training set
Top 0.7%
1.8%
7
BMJ Open
● 601 papers in training set
Top 12%
0.9%
8
IEEE Access
● 35 papers in training set
Top 1%
0.9%
9
PeerJ
◐ 308 papers in training set
Top 10%
0.9%
10
Scientific Reports
○ 3612 papers in training set
Top 71%
0.9%
11
Computers in Biology and Medicine
○ 128 papers in training set
Top 4%
0.9%
12
BMC Medical Informatics and Decision Making
○ 43 papers in training set
Top 2%
0.9%
13
Heliyon
○ 152 papers in training set
Top 7%
0.9%
14
Chaos, Solitons & Fractals
○ 32 papers in training set
Top 0.8%
0.9%
15
PLOS Computational Biology
● 1863 papers in training set
Top 19%
0.9%
16
JMIR Research Protocols
◐ 21 papers in training set
Top 1%
0.6%
17
JMIRx Med
◐ 32 papers in training set
Top 2%
0.6%
18
BMC Medical Education
○ 21 papers in training set
Top 0.7%
0.5%
19
Frontiers in Computational Neuroscience
○ 60 papers in training set
Top 1%
0.5%
20
Infectious Disease Modelling
○ 54 papers in training set
Top 1%
0.5%
21
Neuroscience Letters
○ 32 papers in training set
Top 0.9%
0.5%
22
Cureus
○ 68 papers in training set
Top 5%
0.5%
23
PLOS Global Public Health
● 344 papers in training set
Top 9%
0.5%
24
Briefings in Bioinformatics
◐ 354 papers in training set
Top 8%
0.5%
25
Mathematical Biosciences and Engineering
● 23 papers in training set
Top 1%
0.5%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.