rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Swarm optimization for biomedical applications
  name:
    name part: Mallik, Saurav
    role:
      role term: editor.
  name:
    name part: Taylor & Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2025
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xxiv, 302 pages).
  abstract: "Biomedical engineering (BME) research has been a rapidly growing interdisciplinary research area that provides reasonable solutions to biological and medical problems to improve the healthcare system in recent years. It is connected with various applications like protein structure prediction, computer-aided drug design, and computerized medical diagnosis based on image and signal data, which accomplish low-cost, accurate, and reliable solutions for improving healthcare services. With the recent advancement of machine learning (ML) and deep learning (DL) techniques are widely used in biomedical engineering applications to develop intelligent decision-making healthcare systems in real-time. However, improved accuracy and reliability in model performance can be a significant concern in tackling various types of data generated from medical images and signals, making it challenging for researchers and practitioners. Therefore, optimized models can produce quality healthcare services to handle the complexities involved in biomedical research. Various optimization techniques have been employed to optimize parameters, hyper-parameters, and architectural information of ML/DL models explicitly applied to biological, medical, and signal data. The swarm intelligence approach has recently shown its potential ability to solve complex non-linear optimization problems. It mimics the collective behavior of social swarms such as ant colonies, honey bees, and bird flocks. The cooperative nature of swarms can search global settings of ML/DL models, which efficiently provide the solution to biomedical engineering applications. Finally, our book proposal aims to provide the utility of swarm optimization to design ML/DL models to improve the solutions related to biomedical engineering"--
  table of contents: Preface IntroductionA Swarm Intelligence Optimization for Lung Cancer Detection from RNA-Seq Gene Expression Data Using Convolutional Neural Networks J. Refonaa, S.L. Jany Shabu, Saurav Mallik, S. Dhamodaran, N. Anusha and Mingqiang WangA Comprehensive Review on Optimization Algorithms and Applications for Medical Imaging Data Abhik Sarkar, Md. Yeasin, Dipro Sinha and Nhat Truong PhamA Comprehensive Analysis of Auto Carrier Loading and Cargo Space Optimization for a Specific Type of Container Using GA Kislay Kumar Verma and Babul P. TewariClassification of Heart Disease by Using Particle Swarm Optimization for Hyperparameter Tuning of Machine Learning Models Raagavendran Sundar, Prithiv P., Sarvesh V., Arjun V., Navadeep K.M. and Ashokkumar P.Mathematical Model for Swarm Optimization in Multimodal Biomedical Images M. Thangamani, S. Satheesh, Rajasekhar Lingisetty, Sukumar Rajendran and Basu Dev ShivahareSwarm Intelligence in Lung Cancer Detection and IoT-Enabled Data Transmission: A Technological Approach M. Priyadharshini, V. Murugesh, Ramagiri Praveen Kumar and Kumara Swamy ChunchuRadiant Insights: Unveiling the Future of Cancer Diagnosis through DOTA-NOC and PET-CT Algorithmic Synergy Mandadi Sriya Reddy, Kalyan Chatterjee, Samala Suraj Kumar, Tummala Abhinav Vardhan Reddy, Kumara Swamy Chunchu and Avula SachinSwarm-Optimized Pancreatic Precision: Comprehensive Early Detection through Endoscopic Ultrasound Data Analysis Samala Suraj Kumar, Kalyan Chatterjee, S. Ramchandra Reddy, Tummala Abhinav Vardhan Reddy, Mandadi Sriya Reddy and Avula SachinAn Overview of Optimization Techniques for Pre-processing of RNA-seq Data Subham Ghosh, Dipro Sinha, Md Yeasin, Parinita Das, Saurav Mallik and Guimin QinImproved GA based Clustering with a New Selection Method for Categorical Dental DataAbha Sharma, Pushpendra Kumar, Denny Ben, Meet Bikhani and Rabia Musheer AzizDeepExuDetectNet: Diabetic Retinopathy Diagnosis: Blood Vessel Segmentation and Exudates Disease Detection in …
  target audience: general
  note: editors Saurav Mallik [and 5 others].
  note: "A Science Publishers book."
  note: Includes bibliographical references and index.
  subject:
    topic: Biomedical engineering
    topic: Data processing
  subject:
    topic: Swarm intelligence
  subject:
    topic: Mathematical optimization
  subject:
    topic: Génie biomédical
    topic: Informatique
  subject:
    topic: Optimisation mathématique
  subject:
    topic: COMPUTERS / Computer Graphics / Image Processing (see also PHOTOGRAPHY / Techniques / Digital)
  subject:
    topic: COMPUTERS / Computer Science
  classification: R858.A3
  classification: 610.28
  identifier: 9781032713762
  identifier: 1032713763
  identifier: 9781040324745
  identifier: 1040324746
  identifier: 9781040324738
  identifier: 1040324738
  identifier: 9781032697338
  identifier: 9781032713755
  identifier: 9781032713762 Taylor & Francis
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: TYFRS
    record creation date: 250107
    record change date: 20250319193811.3
    record identifier: in00005620743
    language of cataloging:
      language term: eng