We present evidence that pressures for early childcare may have been one of the driving factors of human evolution. We show through an evolutionary model that runaway selection for high intelligence may occur when (i) altricial neonates require intelligent parents, (ii) intelligent parents must have large brains, and (iii) large brains necessitate having even more altricial offspring. We test a prediction of this account by showing across primate genera that the helplessness of infants is a particularly strong predictor of the adults' intelligence. We discuss related implications, including this account's ability to explain why human-level intelligence evolved specifically in mammals. This theory complements prior hypotheses that link human intelligence to social reasoning and reproductive pressures and explains how human intelligence may have become so distinctive compared with our closest evolutionary relatives.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4922193 | PMC |
http://dx.doi.org/10.1073/pnas.1506752113 | DOI Listing |
J Vasc Access
January 2025
Department of Environmental Sciences, Michigan State University, Lansing, MI, USA.
Objective: Peripheral intravenous catheter (PIVC) failure occurs in approximately 50% of insertions. Unexpected PIVC failure leads to treatment delays, longer hospitalizations, and increased risk of patient harm. In current practice there is no method to predict if PIVC failure will occur until it is too late and a grossly obvious complication has occurred.
View Article and Find Full Text PDFPediatr Res
January 2025
Emma Children's Hospital Amsterdam UMC, location University of Amsterdam, Follow-Me program & Emma Neuroscience group, Meibergdreef 9, Amsterdam, The Netherlands.
Background: Outcome prediction after preterm birth is important for long-term neonatal care, but has proven notoriously challenging for neurocognitive outcome. This study investigated the potential of machine learning to improve neurocognitive outcome prediction at two and five years of corrected age in preterm infants, using readily available predictors from the neonatal setting.
Methods: Predictors originating from the antenatal and neonatal period of preterm infants born <30 weeks gestation were used to predict adverse neurocognitive outcome on the Bayley Scale and Wechsler Preschool and Primary Scale of Intelligence.
Unlabelled: The purpose of this study was to translate and validate a questionnaire to be used by children with chronic diseases during procedures. Specific research questions were as follows: Is the translated versions reliable? Is there a correlation between VCM and another questionnaire measuring discomfort to enhance the validity of VCM? The three versions of Visual CARE measure (VCM) were translated following the principles of good practice for translation and cultural adaptation of patient-reported outcome measures, according to the International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Cognitive debriefing interviews with children, parents, and healthcare professionals were carried out.
View Article and Find Full Text PDFEvol Comput
January 2025
Chair of Algorithms for Intelligent Systems, University of Passau, Passau, Germany
Evolutionary algorithms make countless random decisions during selection, mutation and crossover operations. These random decisions require a steady stream of random numbers. We analyze the expected number of random bits used throughout a run of an evolutionary algorithm and refer to this as the cost of randomness.
View Article and Find Full Text PDFLearn Health Syst
January 2025
Bioethics Research Center, Division of General Medical Sciences, Department of Medicine Washington University School of Medicine St. Louis Missouri USA.
Objectives: Patient engagement is critical for the effective development and use of artificial intelligence (AI)-enabled tools in learning health systems (LHSs). We adapted a previously validated measure from pediatrics to assess adults' openness and concerns about the use of AI in their healthcare.
Study Design: Cross-sectional survey.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!