Table 3 Summary of the included papers that reported on applications towards evaluating response to treatment, symptoms, or underlying pathophysiology together with those for improving measurement tools or support groups. Abbreviations as above in Table 2

Response to treatment

Baranzini et al. [75]

INF-\(\beta\) response

RF;

Accuracy in [75.0%, 82.0%];

CASP2 / IL10 / IL12Rb1.

Ebrahimkhani et al. [76]

microRNA

LR; RF;

AUC in [65.2%, 91.1%].

Fagone et al. [77]

Genomics

UCSC;

Accuracy = 89.2%.

Karim et al. [78]

INF-\(\beta\) response

CART; LASSO; SVM; LR;

Hazard Ratio[4] in [1.359, 1.372].

Kasatkin et al. [79]

Flu-like symptoms

NN; Static Model;

Sensitivity in [73.4%, 81.2%];

Specificity in [71.6%, 80.6%].

Li et al. [80]

Cardiac data

DT;

Baseline hare rate (HR).

Üçer et al. [81]

INF-\(\beta\) response

SNAc; SVM; KNN; RF; NB; LR; DT;

Accuracy in [63.1%, 64.5%];

F1 score in [77.4%, 78.3%];

Walter et al. [82]

Costing data

DT;

NAb is cheaper than other tests.

Patrick et al. [83]

RNAs

GB; LR; RF; LASSO; DA; Nearest SC; WE;

AUC in [72.1%, 89.9%];

Exacerbation of symptoms

Bhattacharya et al. [84]

Daily activities

NN;

Fatigue.

Papakostas et al. [85]

EMG

SVM; RF; ET; Gradient-Boosting;

F1 Score in [75.1%, 77.8%].

Underlying pathophysiology

Chi et al. [86]

Genetic ancestry

LR; RF

HLA-DRB1*15:01 and HLA-DRB1*03:01 alleles.

Forbes et al. [87]

Gut microbiota

RF;

Accuracy in [82.0%, 84.0%];

AUC in [91.0%, 94.0%].

Improve measurement tools

Sébastien et al. [88]

Gait analysis

ET;

Accuracy in [70.9%, 91.7%].

Michel et al. [89]

Quality of life

DT; IRT;

Accuracy in [96.0%, 98.0%].

Improve support groups

Rezaallah et al. [90]

Social media text

NLP; NB;

6 topics related to MS medication.

Deetjen et al. [91]

Text data

LR; NB;

Accuracy in [91.6%, 96.0%];

56% informational and 44% emotional for MS.