Computer Vision News - April 2021

22 Computer Vision Tool The ASD prominence is about six-fold in adults and 2-fold in toddlers comparing to non-jaundice born individuals. According to research, this can be up to 10-fold! Children born with jaundice have a weak link with ASD and it is more common among the males. No w how about the distribution in the population? fig, ax = plt.subplots( 1 , 2 , figsize=( 22 , 8 )) sns.distplot(adults['age'],kde = False, bins= 40 , color='darkred', ax = ax[ 0 ]) ax[ 0 ].set_xlabel('Adult age in years') ax[ 0 ].set_title('Age distribution of ASD positive') sns.distplot(toddles['Age_Mons'], kde = False, bins = 30 , color = 'darkred', ax = ax[ 1 ]) ax[ 1 ].set_xlabel('Toddlers age in months') ax[ 1 ].set_title('Age distribution of ASD positive') Now let’s explore some of the traits included in this dataset. From the earlier exploration, we noticed jaundice, included in those. Jaundice is a yellowing of the skin and the whites of eyes that happens when the body does not process bilirubin properly. The common name is icterus and bilirubin is the yellow-colored waste material that remains in the bloodstream after iron is removed from the blood and it might signal a liver problem. But what’s the relation with ASD? Let’s find out. fig, ax = plt.subplots( 1 , 2 , figsize=( 22 , 8 )) sns.countplot(x='jundice', data = adults, hue = 'gender', ax = ax[ 0 ]) ax[ 0 ].set_title('ASD positive Adults born with jaundice based on gender') ax[ 0 ].set_xlabel('Jaundice while birth') sns.countplot(x = 'Jaundice', data = toddlers, hue = 'Sex', ax = ax[ 1 ]) ax[ 1 ].set_title('ASD positive Toddlers born with jaundice based on gender') ax[ 1 ].set_xlabel('Jaundice while birth')