eChapters

Predictive analytics estimates future health risks and outcomes, while prescriptive analytics recommends appropriate interventions and resource-allocation strategies. This chapter explains how statistical models, machine learning and healthcare data can support disease-risk assessment, prognosis and personalized treatment. Applications involving cardiovascular disease, diabetes, cancer, chronic-disease management and early-warning systems are examined. The integration of clinical, genomic, lifestyle and electronic health-record data is discussed alongside survival analysis, disease-progression modelling and treatment-response prediction. The chapter also addresses bias, fairness, transparency, privacy, regulation and interoperability. Future developments involving real-time analytics, IoT-enabled monitoring and precision medicine illustrate the transition toward proactive, preventive and data-driven healthcare.

Electronic health records contain extensive clinical, demographic, diagnostic and treatment information that can support medical research and decision-making. This chapter examines the characteristics of healthcare big data and the challenges associated with EHR storage, integration, quality and analysis. It presents an analytics pipeline covering data ingestion, secure storage, preprocessing, integration, pattern discovery, visualization and clinical decision support. Machine learning and deep learning methods are discussed in relation to clinical phenotyping, risk stratification, predictive epidemiology and adverse-outcome prediction. The chapter also addresses data privacy, governance, regulatory compliance, explainability, scalability and bias, highlighting the need for secure and interoperable EHR-mining systems that generate clinically useful knowledge.

Symbolic systems provide logical reasoning and explicit knowledge representation, whereas sub-symbolic models offer learning, adaptation and pattern-recognition capabilities. This chapter explains how combining these approaches can create more accurate, adaptive and interpretable intelligent systems. It discusses rule-based systems, logic programming, ontologies, neural networks, fuzzy systems, evolutionary computation and swarm intelligence. Neural-symbolic, neuro-fuzzy, rule-augmented and ontology-aware architectures are examined, along with loose, tight and deep integration strategies. Applications in healthcare, cybersecurity, manufacturing and knowledge-based information systems demonstrate their practical potential. Challenges involving integration complexity, scalability, knowledge engineering, transparency and continuous updating are considered, together with future directions in human-centred hybrid intelligence.

Advanced artificial-intelligence models can achieve high predictive performance, but their black-box nature limits clinical trust and accountability. This chapter examines interpretability and explainability as essential requirements for trustworthy healthcare analytics. It reviews intrinsically interpretable models, post-hoc explanation methods, example-based approaches and network-based explanations. A framework combining data preparation, model selection, ensemble learning, calibration, uncertainty estimation and explanation validation is presented. An explainable sepsis-risk prediction case study demonstrates logistic modelling, ensemble methods, Bayesian uncertainty, SHAP attribution and network analysis. The chapter also addresses causal reasoning, adversarial robustness, temporal and multimodal data, human-centred explainability, ethical responsibilities and regulatory requirements for dependable clinical AI.

Biomedical signals provide valuable information about physiological conditions and support continuous health monitoring. This chapter introduces ECG, EEG, EMG, PPG, respiratory and blood-pressure signals and examines the challenges associated with their acquisition and interpretation. It discusses noise removal, filtering, normalization, resampling and artifact correction before presenting time-domain, frequency-domain, time–frequency, wavelet and nonlinear feature-extraction methods. Feature selection and dimensionality reduction are considered in relation to model accuracy and clinical interpretability. The chapter also explores machine learning, deep learning and hybrid approaches through applications involving arrhythmia detection, seizure prediction and wearable cardiovascular monitoring, highlighting their importance in intelligent and personalized healthcare.

Clinical decision support systems assist healthcare professionals in diagnosis, treatment planning and patient management. This chapter introduces intelligent clinical decision support systems and explains how computational intelligence overcomes the limitations of conventional rule-based approaches. It examines artificial neural networks, fuzzy logic, evolutionary algorithms, swarm intelligence and deep-learning models. A computational architecture integrating clinical data, learning algorithms, fuzzy inference and optimization is presented. Applications in heart-disease diagnosis, diabetes-risk prediction and medical-image analysis illustrate the practical value of these systems. The chapter also addresses interpretability, interoperability, data quality, privacy, legal responsibilities, real-time processing and the challenges involved in deploying intelligent decision-support tools in clinical environments.

Healthcare artificial intelligence depends on the quality, fairness and reliability of the data used for model development. This chapter examines the characteristics of healthcare data and explains how incomplete, inconsistent or unrepresentative datasets can produce inaccurate and discriminatory clinical outcomes. It identifies sampling, demographic, measurement, historical, institutional and annotation biases and discusses strategies for mitigating them at the data, algorithm and evaluation stages. Model robustness across different populations and clinical environments is also considered. Particular attention is given to explainable AI, human oversight, continuous auditing and interdisciplinary collaboration as essential components of trustworthy, equitable and clinically dependable healthcare systems.

This chapter examines the principles, preparation and application of vaccines and biological products. It compares live attenuated, inactivated, toxoid, subunit, recombinant, vector, DNA and mRNA vaccines. Vaccine development phases, immunogenicity, safety, efficacy and post-marketing surveillance are introduced. The chapter discusses adjuvants, including alum, Freund’s adjuvants, liposomes, ISCOMs and delivery systems. Important veterinary vaccines for brucellosis, foot-and-mouth disease, anthrax, Newcastle disease, infectious bronchitis, goat pox, sheep pox and peste des petits ruminants are covered. Questions also address bacterins, toxoids, attenuation, booster requirements and reversion to virulence, providing practical knowledge of immunoprophylaxis in animal-health management.

This chapter deals with the principles and applications of serological tests used to detect antigens and antibodies. It distinguishes primary, secondary and tertiary binding tests and explains antibody titre, affinity, avidity, sensitivity and specificity. Important techniques include precipitation, agglutination, complement fixation, neutralization, immunofluorescence, ELISA, radioimmunoassay, Western blotting and the radioallergosorbent test. The chapter also addresses serum decomplementation and the interpretation of positive and negative reactions. These methods are central to the laboratory diagnosis, surveillance and control of infectious diseases. The objective questions enable readers to compare diagnostic techniques and select appropriate tests according to their principles, applications and analytical performance.

This chapter introduces hybridoma technology and its application in producing monoclonal antibodies. It explains the fusion of antibody-producing B lymphocytes with immortal myeloma cells, selection in HAT medium and the roles of HGPRT and polyethylene glycol. The survival and cloning of hybrid cells and the advantages of monoclonal antibodies are considered. The chapter also discusses tissue and organ transplantation, including autografts, isografts, allografts and xenografts. The immunological mechanisms of acute graft rejection, donor histocompatibility antigens and the involvement of T lymphocytes are addressed. These questions connect laboratory antibody production with transplantation immunology and its diagnostic, therapeutic and research applications.

This chapter examines immune-system failure arising from reactions against self-antigens or inadequate immune responses. It introduces immunological tolerance, central and peripheral tolerance, clonal deletion and clonal anergy. Important autoimmune diseases—including myasthenia gravis, Graves’ disease, systemic lupus erythematosus, multiple sclerosis, rheumatoid arthritis and Sjögren’s syndrome—are considered. The chapter also discusses molecular mimicry and the production of autoantibodies. Primary, secondary and severe combined immunodeficiency disorders are differentiated, with examples such as Chédiak–Higashi syndrome. Immune-privileged sites and immunological paralysis are also covered. These topics explain the mechanisms that normally prevent self-reactivity and the consequences that arise when immune regulation becomes defective.

This chapter explores the four types of hypersensitivity reactions described under the Gell and Coombs classification. Type I immediate hypersensitivity, Type II cytotoxic reactions, Type III immune-complex disease and Type IV delayed hypersensitivity are examined in detail. The roles of IgE, mast cells, basophils, antibodies, complement and T lymphocytes are highlighted. Clinical examples include anaphylaxis, milk allergy, haemolytic disease, transfusion reactions, serum sickness, glomerulonephritis, farmer’s lung and the blue-eye condition associated with canine hepatitis. Diagnostic applications, including the tuberculin and Coombs tests, are also addressed. The chapter explains how exaggerated or inappropriate immune responses can damage tissues and produce disease.

This chapter examines cytokines as essential signalling molecules that regulate immune and inflammatory responses. It introduces interleukins, interferons, chemokines, tumour necrosis factors and colony-stimulating factors. Their sources, target cells and biological actions are considered in relation to immune-cell activation, differentiation, migration and communication. The chapter explains important properties such as pleiotropy, redundancy, synergy and antagonism. It also covers antiviral activity, chemotaxis, inflammation, fever and the regulation of humoral and cell-mediated immunity. Special attention is given to excessive cytokine production, cytokine storms and septic shock. These questions help readers understand how cytokines coordinate protective immunity and contribute to immune-mediated disease.

This chapter introduces the complement system as an important component of innate and adaptive immunity. It explains the classical, alternative and lectin pathways of complement activation and identifies the molecules involved in each pathway. The formation and functions of C3 convertase, C5 convertase and the membrane attack complex are discussed. Questions address complement-mediated cell lysis, inflammation, chemotaxis and opsonization. The roles of C3b, C3a, C4a, C5a, properdin, factor H and other regulatory proteins are also examined. By covering the activation and regulation of complement, the chapter explains how this system enhances antibody activity and helps eliminate invading microorganisms

This chapter explains how B-cell receptors, T-cell receptors and major histocompatibility complex molecules participate in antigen recognition. It differentiates MHC class I and class II pathways and describes the processing of endogenous and exogenous antigens. The roles of dendritic cells, macrophages and B lymphocytes as professional antigen-presenting cells are examined. Topics include MHC restriction, antigenic peptides, proteasomal degradation, ubiquitination and recognition by CD4-positive and CD8-positive T lymphocytes. The chapter also discusses superantigens, opsonization, phagocytosis, T-independent antigens and species-specific MHC systems such as BoLA and the avian B complex. These concepts explain the initiation of adaptive immune responses.

This chapter focuses on the structure, classes, properties and biological functions of immunoglobulins. It introduces the basic antibody molecule, including heavy and light chains, variable and constant regions, antigen-binding sites and Fc fragments. The characteristics of IgG, IgM, IgA, IgE and IgD are examined in relation to their distribution and immune functions. Questions cover primary and secondary immune responses, placental transfer, mucosal protection, allergic reactions, complement activation and agglutination. The chapter also addresses antibody affinity, avidity, isotypes, allotypes, idiotypes, class switching and Bence-Jones proteins. It provides essential knowledge of how antibodies recognize antigens and contribute to immune protection and diagnosis.

This chapter describes the cells, tissues and organs responsible for immune defence. It examines lymphocytes, macrophages, dendritic cells, neutrophils, mast cells, natural killer cells and plasma cells, emphasizing their respective functions. Primary and secondary lymphoid organs—including bone marrow, thymus, bursa of Fabricius, spleen, lymph nodes and mucosa-associated lymphoid tissue—are discussed. The chapter also covers lymphocyte maturation, antigen presentation, phagocytosis, immune-cell surface markers and the organization of lymph-node regions. Positive and negative selection of T lymphocytes and the formation of memory cells are included. Together, these topics explain how immune components develop, communicate and coordinate effective responses against infectious agents.

This chapter examines the major forms and mechanisms of immunity. It distinguishes innate immunity from adaptive immunity and explains specificity, diversity, immunological memory and self–non-self recognition. Natural and artificial forms of active and passive immunity are discussed through examples involving infection, vaccination, maternal antibodies and antiserum administration. The chapter introduces pattern-recognition receptors, pathogen-associated molecular patterns and Toll-like receptors involved in microbial recognition. It also covers inflammation, its cardinal signs, acute-phase proteins and the roles of neutrophils and other innate defence components. These objective questions provide a clear foundation for understanding how animals resist infections and develop long-lasting protective immune responses.

This chapter introduces the historical development and fundamental concepts of immunology. It highlights the contributions of Edward Jenner, Louis Pasteur, Elie Metchnikoff, Paul Ehrlich, Emil von Behring and other pioneering scientists. Important discoveries related to vaccination, phagocytosis, antibody formation, cellular immunity, ELISA, radioimmunoassay and hybridoma technology are addressed. The chapter also explains antigens, immunogens, epitopes, haptens, adjuvants and the desirable characteristics of an effective immunogen. Questions concerning smallpox and rinderpest eradication, vaccine development and primary and secondary immune responses help readers understand the scientific milestones that established immunology as an essential discipline within veterinary and biomedical sciences.

The phases of green revolution and post green revolution of Indian agriculture have assured us of security. We are now producing 354 million tons of food grains and our target is to produce 550 million tons before 2050. This is really an incredible progress for any country dominating with rural and agrarian economy. As on date, the contribution of Indian agriculture to national GDP is 14.7 % but it has to support around 60% of population. While food security has been ensured for 1480 million of population, the issues of malnutrition are standing paramount. It sounds melancholic that India is also sustaining world’s highest count of hungry population close to 51% newborn babies are underweight, 60% of rural women are anaemic, millions are deprived of dedicated safe drinking water. According to FAO, between 702 and 828 million people in the world faced hunger in 2021. Health, hygiene and nutrition are organically linked to each other, in terms of calorie intake of rural women. We are still far below of international standard. Alongside, the hemoglobin level runs below the expected level to indicate that women are runningin a moderate to acute anaemic condition. Around 840 million people are malnourished from insufficient calories. According to Black et al., (2008) nutrition related factors were found to be jointly responsible for around 35% of the child fatalities and 11% of the overall global illness burden in an analysis that took into account co-exposure. Due to poor quality of drinking water, whatever available, the propagation of water born diseases has been endemic and robust. The geo-spatial distribution of hunger and malnutrition indicates that there is location to location variation, gender discrimination, and seasonal variability across the terrain of social-cultural distribution. To make India stronger and swashbuckling we need to refocus on women health, child care and removal of economic discrimination. With acute hunger, mapping, problem of chronic hunger as well, chronic hunger hasbeen reflected through seasonal sickness, broken health and psycho-somatic downfall. Sometimes, poverty has not been the only factor for malnutrition. The other factors for malnutrition can be our wrong belief system, superstition, wrong food habit, and unscientific cooking process. With this background the objectives of the studyhave been spelt out.