Authors/Year NMR Applications n-Dimensional Machine Learning Advantageous Weakness
Wishart (2008)[19], Karaman (2015)[36], Rocha (2018)[35] spectroscopy metabolomics 2D PCA/PLA informative slow
Frydmann (2014)[30] spectroscopy ultrafast NMR 2D no rapid gradient field
Qu (2019)[18] spectroscopy generic n-dimensional deep learning speed up information lose?
Haun (2010)[40], Haun[20] (2011), Liong (2013)[37], Peng (2014)[21], Neely (2016)[41], Robinson (2017)[42] relaxometry medical diagnosis 1D no rapid, PoCT low specificity and sensitivity, missing out cross peaks?!
Robinson (2014)[43], Ok (2016)[44]
relaxometry
food science
1D
no
rapid, PoCT
Santos (2016)[45], Zhu (2016)[38]
relaxometry
food science
1D
PCA/PLA
rapid, PoCT
Xu (2014)[46], Rudszuck (2019)[27]
relaxometry
food science
2D
no
PoCT, high specificity and sensitivity
slow
Hurlimann (2002)[47] relaxometry oil-gas exploration 1D, 2D no in situ, high specificity and sensitivity slow
Lewis (2013)[48] relaxometry oil-gas exploration 2D no slow
Birdwell (2015)[49] relaxometry oil-gas exploration 2D PCA/PLA slow
Clustering NMR (2020)
relaxometry-clustering
generic
(pseudo) n-dimensional
clustering analysis, supervised model
rapid, PoCT, high specificity and sensitivity
missing out cross peaks?