In recent years the issue of low birth rates become more and more serious in many countries. In 2017, the average birth rate is 1.17 for every child-bearing woman in Taiwan, ranking the last among Asian countries. As the declining birth rates, the population of Taiwan will decrease year by year while showing an aging society. It will be an important crisis in Taiwan's future development. Although the declining birth rates in Taiwan year by year, the incidence of premature has not decrease. Moreover, the morbidity and long-term prognosis of preterm infants, will be a significant burden of children, families, and national economy. Therefore, it should be a serious issue of government. According to the above reasons, to keep the safe pregnancy and normal development of the fetus, smooth delivery and even postpartum newborn healthy growth and so on, will be very important issues in the future.~Due to advances in medical technology and the improvement of newborn care, makes the very low birth weight preterm infant survival rate greatly improved. However, the improvement of survival rate did not improve the incidence of postnatal morbidity of the preterm infants, and the risk of many neurodevelopmental disorders greatly increased. Many studies have confirmed the long-term prognosis of preterm infants with low birth weight, whom with serious abnormalities in neurocognitive development, language development, motor development and so on. Attention deficit hyperactivity disorder (ADHD) and Autism spectrum disorder (ASD) are common neurodevelopmental disorders. These deficiencies such as inattention, decreased learning ability, behavioral problems and social skills disturbance ....make the children have poor outcome. It is affect children academic achievement and adaptation so great in the future. Therefore, the government, experts and scholars should concern about the issue of the premature and these pediatric neurological development delay and poor prognosis.~Meanwhile, this study will design a 5-year retrospective and prospective case control study, will include 650 participant. And participants will be divided into four groups:(a) Premature children with neurological developmental disorder (such as ADHD): n = 200; (b) Premature children with neurological developmental disorder (such as ASD): n = 50; (c) Premature infants with no neurodevelopmental disorders: n = 200; (d) Age and gender match in non-preterm children: n = 200.~By this research to achieve the aims: (1) Through the cross-sectional analysis of this study, the investigators can understand the current prevalence of developmental disorders in Taiwan ,especially ADHD and ASD, and the ratio of male to female in school-age children. (2) Analysis of risk factors in preterm infants during pregnancy and infant, and construct the diagnostic predictive models. (3) By the cohort study of premature infants, to analyze early risk factors of premature children with neurological developmental disorders (such as ADHD), and develop the diagnostic predictive models and early interventional tools. (4) Using artificial intelligence and machine learning analysis to analyze the characteristics of preterm and development of diagnostic prediction model of premature infant or premature children combined ADHD. (5) The application of noninvasive physiological signal capture real-time analysis system in screening and evaluation of premature infant and neurodevelopmental disorders.
The study will be a 5-year retrospective and prospective case control study, included 650 participants, and participants will be divided into four groups.By this research the investigators will achieve several aims:(1) Through the cross-sectional analysis of this study, the investigators can understand the current prevalence of developmental disorders in Taiwan ,especially ADHD and ASD, and the ratio of male to female in school-age children. (2) Analysis of risk factors in preterm infants during pregnancy and infant, and construct the diagnostic predictive models. (3) By the cohort study of premature infants, to analyze early risk factors of premature children with neurological developmental disorders (such as ADHD), and develop the diagnostic predictive models and early interventional tools. (4) Using artificial intelligence and machine learning analysis to analyze the characteristics of preterm and development of diagnostic prediction model of premature infant or premature children combined ADHD. (5) The application of noninvasive physiological signal capture real-time analysis system in screening and evaluation of premature infant and neurodevelopmental disorders.