Woodland Steps Learn
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Integrative Machine Learning and Optimization Algorithms for Disease Prediction
Author: Muniasamy, Anandhavalli
language: en
Publisher: IGI Global
Release Date: 2025-07-03
Integrative approaches that combine machine learning (ML) and optimization algorithms rapidly transform the landscape of disease prediction and healthcare analytics. By leveraging the predictive power of ML models alongside the efficiency of optimization techniques, researchers can develop more accurate, robust, and scalable systems for early diagnosis and risk assessment. These hybrid frameworks enable the integration of diverse data sources into cohesive predictive models. The synergy between ML and optimization enhances model performance while supporting personalized medicine by tailoring predictions to individual patient profiles. Integrative methodologies hold significant promises for advancing clinical decision-making and improving health outcomes. Integrative Machine Learning and Optimization Algorithms for Disease Prediction explores the cutting-edge applications of machine learning, deep learning, and optimization algorithms in disease prediction. It examines how diverse machine learning models, from traditional algorithms to deep learning and ensemble methods, can be optimized for high-stakes clinical predictions. This book covers topics such as disease prediction, healthcare data, and mental health, and is a useful resource for computer engineers, medical professionals, academicians, researchers, and scientists.
Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems
The consideration of symbolic machine learning algorithms as an entire class will make it possible, in the future, to generate algorithms, with the aid of some parameters, depending on the initial users' requirements and the quality of solving targeted problems in domain applications. Diagnostic Test Approaches to Machine Learning and Commonsense Reasoning Systems surveys, analyzes, and compares the most effective algorithms for mining all kinds of logical rules. Global academics and professionals in related fields have come together to create this unique knowledge-sharing resources which will serve as a forum for future collaborations.
Leading a School Culture of Learning
This practical book is designed to help school leaders develop a sustainable culture of learning across the curriculum. It offers a personal insight into how one school embraced a range of dialogic and analytical tools to create an environment in which all stakeholders were inspired to evaluate and innovate. Each chapter tackles one piece of the ‘jigsaw’ that makes up a successful school environment, considering topics such as Attitudes for Learning, Coaching for Learning and Love of Learning. Utilising theory, case studies and activities, it illustrates how the reader can realistically and practically increase student attainment in their own school setting. This book will help leaders: Develop a supportive and encouraging leadership style that will create a cycle of self-improvement and self-efficacy for all Adapt the curriculum to focus on progress and engagement Use the Philosophy 4 Children strategies to promote deeper thinking and enquiry, increasing the rate of school improvement through a system of enquiry based staff professional development Using an inner-city primary school as a working example, this book will be a source of inspiration and encouragement for school leaders, teachers and school advisors looking to cultivate and embed a love of learning into their school.