Machine learning and its applications to healthcare Millie Pant, Kusum Deep, Atulya K. Nagar, editors

Format:

Book

Author/Creator:

Pant, Millie

Contributor:

Pant, Millie, 1979- editor.

Deep, Kusum, editor.

Nagar, Atulya K., editor.

Series:

Mathematics for sustainable developments 3004-9024

Language:

English

Subjects (All):

Machine learning.

Artificial intelligence--Medical applications.

Artificial intelligence.

Machine Learning.

Medical Subjects:

Machine Learning.

Physical Description:

1 online resource

Place of Publication:

Singapore Springer [2026]

System Details:

text file PDF

Summary:

This book offers a comprehensive collection of 35 research contributions on the transformative role of soft computing techniques such as fuzzy logic, neural networks, genetic algorithms, and hybrid methodologies in solving complex problems in healthcare. By aligning its themes with Sustainable Development Goals (SDG 3: Good Health and Well-Being), the book offers a comprehensive analysis of how these technologies are being integrated into medical diagnosis, predictive modeling, disease classification, personalized medicine and healthcare management. Through an exploration of current trends, research advancements and practical implementations, the book demonstrates the immense potential of soft computing to improve healthcare outcomes. It features a wide array of applications, including diagnostic systems for diseases such as cancer, Alzheimer's and cardiovascular conditions, as well as personalized treatment recommendations, patient monitoring systems and medical image analysis. It is aimed at researchers, practitioners and healthcare professionals, seeking to explore and apply advanced computational techniques to the medical field, providing both theoretical insights and practical applications

Contents:

Assessing Students Emotions in Learning Environment Integrating Deep Learning with Statistical Learning

MediAI A Specialized Medical LLM for Accurate Diagnosis and Clinical Documentation

Predicting Maternal Health Risks using Ensemble Model Multilayer Perceptron and PCA Features

Performance Evaluation of Deep Learning Models using Transfer Learning on Ultrasound Images for Breast Cancer Detection

Identification of Severity of Chronic Obstructive Pulmonary Disease COPD using Machine Learning Models based on Spirometry Data

Real time Healthcare Environment Monitoring Through Deep Learning A Multi Modal Sensor Fusion Implementation

EMG Signal Classification in Lower Limbs using Machine Learning Techniques

Real time Virtual Meeting Architecture for Deaf People Audio Transcription Noise Processing and Sign Language Translation using LSTM Neural Networks

Predictive Modeling of Sepsis Risk Leveraging Clinical Parameters for Early Detection and Intervention

A Targeted Study of Lightweight Machine Learning Techniques for Cardiac Arrhythmia Risk Prediction

Development of Smart ECG Monitoring System using IoT and ML

AI Driven Pneumonia Diagnosis Harnessing Custom CNNs for Chest X ray Analysis

A Serverless Cloud Approach to a Scalable Geospatial Healthcare Web based Application

Ensemble Learning Inspired Model for Medical Image Segmentation

A Non local Weighted Optical Flow based CNN Model for Smoke Detection using Static and Dynamic Features

Behavioral Analysis Techniques for Early Detection of Ransomware

Machine Learning based Diabetic Prediction on Indigenous Shakti Processor for Edge Health Monitoring

Skin Lesion Segmentation using UNet based Architectures

Bridging Molecular Features and Solubility Towards Drug Design A Machine Learning Framework for Solubility Prediction Ensemble Model Based Fall Detection on Elderly Adult using CNN BILSTM

AI based Automated ICD Coding for Clinical Texts and Records A Systematic Literature Review

A Hybrid CNN LSTM Model for Sudden Cardiac Death Prediction

Hybrid Deep Learning Model for Fall Detection in Healthy Elderly using CNN BiLSTM CNBiLS

Fake News Detection using Machine Learning and Sentiment Analysis Integrated in a Flask Web Application

Early stage Detection for Alzheimer Disease using Machine Learning and Deep Learning Algorithm

Advanced Machine Learning Framework for Early Detection of Cardiac Disease using Statistical Analysis and Feature Engineering

Optimum Hyperbolic Tangent Function for MRI Enhancement

Towards a More Competent Healthcare System A Methodological Approach for Quantizing Reliable Detection of Concealed Depression using Ensemble Learning

Diabetes Risk Progression and Personalized Recommendations using Machine Learning

Alzheimers Disease Prediction using Convolutional Neural Network

Hybrid Generative AI Framework for Medical Text Summarization Enhancing Precision and Relevance in Healthcare Decision Making

Multi Modal Hybrid Model for Depression Detection on Social Media and Clinical Datasets

Design of an Improved Method for PET Scan Analysis using ConvTransformers and SHAP Guided Ensembles for Oral Cancer Diagnosis

Transforming Healthcare with AI A Comprehensive Review of Innovations in Tropical Disease Management and Cancer Therapy

Brain Tumor Classification using a CNN Driven Deep Learning Framework Leveraging MRI Imaging

Edge Detection in Medical imaging via Clustering A Quantum Computing Approach for Lung Carcinoma and Brain Tumor

Alzheimer Disease Classification using Transfer Learning of Pre trained Model

Human centric Medical Summarization with Hybrid Generative AI

Predictive Analysis of Drug Impact using GNN

Evaluation of Side Effects Associated with Covid 19 Vaccines india

Notes:

Online resource; title from PDF title page (SpringerLink, viewed May 26, 2026)

ISBN:

9789819548316

9819548314

OCLC:

1592861331