Autore	Raza Khalid
Edizione	[1st ed. 2024.]
Pubbl/distr/stampa	Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica	1 online resource (335 pages)
Disciplina	006.3
Altri autori (Persone)	SinghSurender
Collana	Studies in Computational Intelligence
Soggetto topico	Computational intelligence Artificial intelligence Medical informatics Quantitative research Computational Intelligence Artificial Intelligence Health Informatics Data Analysis and Big Data
ISBN	9789819990290 9819990297
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Autoimmune Disorders: Types, Symptoms and Risk Factors -- Immune System and Autoimmunity: Cellular and Molecular Mechanisms -- Autoimmune Diseases: Recent Insights on Epidemiology, Pathogenesis and Prevalence Rate -- The Role of Artificial Intelligence and Machine learning in Autoimmune Disorders -- Autoimmune Autonomic Disorder: AI-based Diagnosis and Prognosis -- Detection of Rheumatoid Arthritis using CNN in Autoimmune Diseases Disorders -- The Emerging Applications of Machine Learning in the Diagnosis of Multiple Sclerosis -- Exploring State-of-the-art CNN Models for Early Detection of Multiple Sclerosis using MRI Images -- AI-assisted Model for Risk Detection of Autoimmune Diseases -- Artificial Intelligence in the Diagnosis and Treatment of Rheumatoid Arthritis: Current Status and Future Perspectives -- Data Analytics for Diagnosis, Tracking, and Treatment Planning in Autoimmune Diseases using AI -- Role of Artificial Intelligence in the Treatment Management of Psoriatic Arthritis -- Artificial Intelligence, Machine Learning and Deep Learning in the Diagnosis and Treatment of Rheumatoid Arthritis: Case Studies -- Artificial Intelligence and Machine Learning Techniques in the Diagnosis of Type I Diabetes: Case Studies -- Computational Intelligence Methods for Biomarkers Discovery in Autoimmune Diseases: Case Studies -- AI-empowered Prediction of Prognosis and Treatment Response in Rheumatoid arthritis.
Record Nr.	UNINA-9910838276603321

Autore	Raza Khalid
Edizione	[1st ed. 2023.]
Pubbl/distr/stampa	Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2023
Descrizione fisica	1 online resource (340 pages)
Disciplina	570.285
Collana	Studies in Computational Intelligence
Soggetto topico	Computational intelligence Artificial intelligence Medical informatics Cancer - Genetic aspects Bioinformatics Computational Intelligence Artificial Intelligence Health Informatics Cancer Genetics and Genomics Computational and Systems Biology
ISBN	9789811963797 9789811963780
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Part-I: Preliminaries -- Chapter 1. The Scope and Applications of Nature-Inspired Computing in Bioinformatics -- Chapter 2. Leveraging Healthcare System with Nature-Inspired Computing Techniques: An Overview and Future Perspective -- Part-II: Nature-Inspired Computing in Cancer Research -- Chapter 3. Nature-Inspired Computing in Breast Cancer Research: Overview, Perspective and Challenges of the State-of-the-art Techniques -- Chapter 4. Advances in Genomic Profiling of Colorectal Cancer using Nature[1]Inspired Computing Techniques -- Chapter 5. Potential Role of the Nature-Inspired Algorithms for Classification of High-dimensional and Complex Gene Expression Data -- Chapter 6. Optimized Nature-Inspired Computing Algorithms for Lung Disorder Detection -- Chapter 7. Overview and Classification of Swarm Intelligence-based Nature[1]Inspired Computing Algorithms and their Applications in Cancer Detection and Diagnosis -- Chapter 8. Nature-Inspired Computing: Scope and applications of Artificial Immune Systems towards Analysis and Diagnosis of Complex Problems -- Chapter 9. Nature-Inspired Computing: Bat echolocation to BAT algorithm -- Chapter 10. Social, Emotional and Ethical (SEE) Attributes, Which Configures Our Bioinformatics Systems to Activate the Hidden Forces to Shape Human Decisions -- Part III: Nature-Inspired Computing in Drug Design, Development, and Therapeutics -- Chapter 11. Applications of Nature-Inspired Computing and Artificial Intelligence Algorithms in Solving Personalized Therapy Complications -- Chapter 12. Role of Nature-Inspired Intelligence in Genomic Diagnosis of Antimicrobial Resistance -- Chapter 13. Consequential Innovations in Nature-Inspired Intelligent Computing Techniques for Biomarkers and Potential Therapeutics Identification -- Chapter 14. Nature-Inspired Computing Techniques in Drug Design, Development, and Therapeutics -- Chapter 15. Illustrious Implications of Nature-Inspired Computing Methods in Therapeutics and Computer-Aided Drug Design -- Chapter16. Nature-based Computing Bioinformatics Approaches in Drug Discovery against Promising Molecular Targets Carbonic Anhydrases and Se[1]rine/Threonine Kinases for Cancer Treatment.
Record Nr.	UNINA-9910629298303321

Autore	Raza Khalid
Edizione	[1st ed. 2024.]
Pubbl/distr/stampa	Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024
Descrizione fisica	1 online resource (212 pages)
Disciplina	006.3
Collana	Springer Tracts in Nature-Inspired Computing
Soggetto topico	Computational intelligence Artificial intelligence Image processing Computational Intelligence Artificial Intelligence Image Processing
ISBN	9789819773442 981977344X
Formato	Materiale a stampa
Livello bibliografico	Monografia
Lingua di pubblicazione	eng
Nota di contenuto	Fundamentals of Artificial Bee Colony Algorithms and Its Variants -- The Rise of Artificial Bee Colony Algorithms in Data Science and Machine Learning is Notable -- Swarm Intelligence for Optimization: A Bee's-Eye View on Multi-objective and Dynamic Challenges -- Artificial Bee Colony Algorithms in Control Systems, Robotics and Automation -- Integrating Artificial Bee Colony Algorithms for Deep Learning Model Optimization: A Comprehensive Review -- An IoMT Enabled Iterative Artificial Bee Colony Approach Using Federated Learning for Detection of Heart Disease -- Optimal Design of a Biomedical Amplifier for Minimum Offset Using a Modified ABC Algorithm -- Using Honeybees for Gene Expression Profiling: The Artificial Bee Colony Algorithm to Identify Robust Gene Biomarkers for Clinical Diagnosis -- Smart Diagnostics for Diabetic Retinopathy: Integrating Artificial Bee Colony Algorithms into Medical Image Analysis -- Artificial Bee Colony Algorithms in Gene Expression Studies: A Case Study -- Artificial Bee Colony Algorithm in Multi-Omics Analysis: A Case Study.
Record Nr.	UNINA-9910913787103321