Table 4 Studies classified as per domains of applications of artificial intelligence in orthodontics

a. For orthodontic extractions

5

[18, 23, 25, 28, 68]

b. For TMJ Osteoarthritis

4

[22, 47, 66, 67]

c. To assess maxillary constriction and/or impacted canines

3

[51, 54, 71]

d. For screening of osteoporosis from panoramic radiographs

2

[34, 41]

e. Assessment for need for orthodontic treatment and/or prediction of treatment outcome

2

[42, 53]

f. Classification of skeletal patterns

2

[24, 44]

g. Prediction of orthodontic treatment outcome—class III M/O

2

[46, 62]

h. For orthognathic surgery and orthodontic extractions

1

[21]

i. To assess airflow dynamics, predict upper airway collapsible sites and obstructive sleep apnea

1

[40]]

j. To predict association between C. difficile infections in hospitalized patients with major surgeries

1

[52]

k. Genetic risk assessment for non-syndromic orofacial cleft

1

[48]

l. To predict occurrence of obstructive sleep apnea in patients with Down’s syndrome

1

[72]

m. Evaluation of facial attractiveness

1

[45]

n. Trainers for clenching

1

[29]

o. Selection of orthodontic appliance- type of headgear

1

[63]

p. Quantification of sagittal skeletal discrepancy

1

[49]

q. For cases suitable for fixed mechanotherapy

1

[55]

r. Selection of patients suitable to be treated with removable orthodontic appliances

1

[56]

s. Class II division 1 malocclusion

1

[57]

t. Broad-based

1

[79]

a. Lateral cephalogram

12

[27, 32, 35, 37, 64, 65, 69, 70, 74, 75, 77, 78]

b. CBCT images

6

[31, 58,59,60,61, 76]

c. Frontal cephalogram

1

[19]

a. Cervical vertebra maturation

1

[18]

b. Broad-based

3

[30, 39, 73]

Evaluation of treatment outcome- orthognathic surgery on facial appearance/ attractiveness and/or age perception

2

[36, 38]

a. Tooth segmentation from CBCT images/model

2

[33, 43]

b. Detection of activation pattern of tongue musculature

1

[50]

c. Evaluation of temperature changes during curing for orthodontic bonding

1

[26]