machine learning models are built. you’ll utilize python code with tools like tensorflow to explore essential neural network design. develop a fundamental coding skill set, train and test models, and learn how to solve complex problems. along the way, you'll work with world-class data sets ...
Learning machine learning with young children: exploring informal settings in an African contextIsmaila Temitayo SanusiKissinger SundaySolomon Sunday OyelereJarkko SuhonenHenriikka VartiainenMarkku Tukiainen
It is important for clinical practice to differentiate between conditions displaying similar symptoms via established diagnostic instruments. Applying the LightGBM algorithm in machine learning, we were able to differentiate subjects with ADHD, obesity, problematic gambling, and a control group using all ...
In this paper, we built machine learning models for predicting suicidal behavior among children and adolescents based on their longitudinal clinical records, and determining short- and long-term risk factors. This retrospective study used deidentified structured electronic health records (EHR) from the ...
Many adolescents experience depression that often goes undetected and untreated. Identifying children and adolescents at a high risk of depression in a timely manner is an urgent concern. While the Children’s Depression Inventory (CDI) is widely utilize
Machine learning systems are infiltrating our lives and are beginning to become important in our education systems. This article, developed from a synthesi
Teen Academy Machine Learning & Data Science Academy with Python Ages 13-18 Beg-Adv Teen Academy AI and Machine Learning Academy with NVIDIA Ages 13-18 Beg-Adv Tech Camp Artificial Intelligence and Machine Learning Ages 13-17 Int-Adv
Handwritten forensic analysis or handwriting recognition using machine learning (ML) algorithms can be a great solution to classify adults and children based on their handwritten text and handwritten pattern. Ahmad et al. (2004) proposed support vector machine (SVM) with some kernels for online ...
childhood obesity;BMI;machine learning;EHR 1. Introduction While previously uncommon in young children, obesity is now a worldwide epidemic affecting over 40 million children under the age of 5 [1,2]. Obesity in childhood is associated with both adverse outcomes like hyperlipidemia, diabetes and ...
Explore advancements in state of the art machine learning research in speech and natural language, privacy, computer vision, health, and more.