82. Poor reporting of methods and performance measures by machine learning studies in orthopedic surgery: A systematic review

2021 ◽  
Vol 21 (9) ◽  
pp. S40
Author(s):  
Olivier Groot ◽  
Joseph H. Schwab ◽  
Neal Kapoor ◽  
Michiel Bongers
2022 ◽  
pp. 24-56
Author(s):  
Rajab Ssemwogerere ◽  
Wamwoyo Faruk ◽  
Nambobi Mutwalibi

Classification is a data mining technique or approach used to estimate the grouped membership of items on a basis of a common feature. This technique is virtuous for future planning and discovering new knowledge about a specific dataset. An in-depth study of previous pieces of literature implementing data mining techniques in the design of recommender systems was performed. This chapter provides a broad study of the way of designing recommender systems using various data mining classification techniques of machine learning and also exploiting their methodological decisions in four aspects, the recommendation approaches, data mining techniques, recommendation types, and performance measures. This study focused on some selected classification methods and can be so supportive for both the researchers and the students in the field of computer science and machine learning in strengthening their knowledge about the machine learning hypothesis and data mining.


2006 ◽  
Vol 25 (3) ◽  
pp. 253-270 ◽  
Author(s):  
Liliana Coman ◽  
Julie Richardson

ABSTRACTThe authors conducted a systematic review of studies examining correlations between assessments of function obtained using self-report and those obtained using performance-based measures for community-dwelling older adults.METHODSArticles for this review were identified using electronic searching in MEDLINE, CINHAL, and AGELINE and hand-searching techniques. Two reviewers selected the studies that met the inclusion criteria, extracted the data, and assessed the methodological quality of the data.RESULTSSeventeen studies met the inclusion criteria for review. Correlations between self-report and performance ranged from −0.72 to 0.60. Sixty per cent of the studies compared self-report instruments measuring disability with performance measures addressing functional limitations. In studies that assessed the same functional tasks and functional limitations using the two methods, the correlation varied between 0.60 and 0.86.CONCLUSIONWhen the construct measured by the two methods was the same, the correlations were moderate to large and, therefore, measurement of functional limitations by self-report or performance probably reflected a similar assessment of function.


2021 ◽  
Vol 13 (1) ◽  
pp. 11-19
Author(s):  
Mingxing Gong

Machine learning models have been widely used in numerous classification problems and performance measures play a critical role in machine learning model development, selection, and evaluation. This paper covers a comprehensive overview of performance measures in machine learning classification. Besides, we proposed a framework to construct a novel evaluation metric that is based on the voting results of three performance measures, each of which has strengths and limitations. The new metric can be proved better than accuracy in terms of consistency and discriminancy.


2019 ◽  
Vol 49 (5) ◽  
pp. 763-782 ◽  
Author(s):  
Jayme R. Miller ◽  
Bas Van Hooren ◽  
Chris Bishop ◽  
Jonathan D. Buckley ◽  
Richard W. Willy ◽  
...  

2017 ◽  
Vol 73 (2) ◽  
pp. 297-305 ◽  
Author(s):  
A L Bienvenu ◽  
L Argaud ◽  
F Aubrun ◽  
J L Fellahi ◽  
C Guerin ◽  
...  

Author(s):  
Olivier Q. Groot ◽  
Paul T. Ogink ◽  
Amanda Lans ◽  
Peter K. Twining ◽  
Neal D. Kapoor ◽  
...  

2015 ◽  
Vol 4 (1) ◽  
Author(s):  
S. Abolfazi Soltani ◽  
Armann Ingolfsson ◽  
David A. Zygun ◽  
Henry T. Stelfox ◽  
Lisa Hartling ◽  
...  

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