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Step 2, feature extraction, then extracts this information in order to assign it to one abnormality type using the classification method used in Step 3. Research on EEG abnormalities detection is wide and varied, but almost in all previous studies, a single channel signal analysis approach is used (see Section 1.3).
The design of a novel approach for automatic abnormalities detection and localization using a multichannel EEG signal for newborn is necessary to help the specialists to detect the presence of different abnormalities by interpreting the EEG signal in terms of abnormality type and its source localization, and to decide on a suitable diagnosis.
We first used logistic regression with stepwise selection to identify factors that were significant predictors for each abnormality type (skeletal and eye abnormalities).
The rarest abnormality type was polymelia (extra limb); only one specimen had an extra limb, and this frog was also found in Kenai.
The preliminary logistic regression analysis identified significant differences in skeletal abnormalities among refuges; however, once we accounted for autocorrelation in our data with the repeated-measures analysis, refuge was no longer a significant predictor of any abnormality type.
First, we evaluated individuals with each abnormality type across sites with Kruskal-Wallis one-way analysis of variance (ANOVA) to determine if the occurrence of specific abnormalities differed across sites.
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Interestingly, Table 2 shows a different distribution of chromosomal abnormality types according to the indication.
Several abnormality types occurred only in Kenai, including anteversion (twisted long bones), microcephaly (shrunken head), scoliosis (curved spine), cutaneous fusion (skin webbing), and kinked tail (Table 2).
Shrunken and partial limbs were among the most common abnormality types at all refuges except Innoko, which had a high proportion of partial limbs (27% of the abnormalities were of this type) but fewer shrunken limbs (only 7% of the abnormalities at this refuge).
17 Other collagen gene mutations are reported to be associated with oral and dental abnormalities: type I collagen chain gene mutations are associated with type I dentinogenesis imperfecta in the more general context of osteogenesis imperfecta.
25 Clinical records of NICU hospitalisation will be reviewed by the interviewers to retrieve data on pregnancy complications (gestational hypertensive disorders, gestational diabetes and placental abnormalities), type of delivery and neonatal characteristics (birth weight and height, gestational age and cephalic perimeter) of very preterm infants.
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