1st Edition

AI for Immunology




  • Available for pre-order. Item will ship after January 28, 2021
ISBN 9780367654658
January 28, 2021 Forthcoming by Chapman and Hall/CRC
120 Pages 11 B/W Illustrations

USD $19.95

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Book Description

The bioscience of immunology has given us a better understanding of human health and disease. Artificial intelligence (AI) has elevated that understanding and its applications in immunology to new levels. Together, AI for immunology is an advancing horizon in health care, disease diagnosis, and prevention. From the simple cold to the most advanced autoimmune disorders and now, pandemics, AI for immunology is unlocking the causes and cures.

Key features:

  • a highly accessible and wide-ranging short introduction to artificial intelligence for immunology.
  • includes a chapter on COVID-19 and pandemics.
  • includes scientific and clinical considerations as well as immune and autoimmune diseases.

Table of Contents

Title Page

Dedication Page

Preface

Table of Contents

Chapter One:  Understanding Artificial Intelligence (AI)

A.      Introduction

B.      A model for understanding artificial Intelligence

C.      AI Hardware

1.      Ram (Random access memory)

2.      Central Processing Unit (CPU)

3.      Graphic Processing Unit (GPU)

4.      Servers

5.      Internet of Things (IoT)

D.      AI Software (Algorithms)

1.      Application Programming Interface (API) 

2.      Artificial Neural Network (ANN)

a.     Machine Learning

1)    Supervised (labeled) data

b.     Deep Learning

1)    Unsupervised (unlabeled) data

2)    Reinforcement learning

E.      AI-related computer systems

1.      Natural Language Processing (NLP)

2.      Expert Systems

3.      Big Data Analytics

4.      Immunoinformatics

 

Chapter Two: AI and the bioscience and clinical considerations for immunology

A.     Introduction

B.     Innate (natural) immunity

1.       Cellular and humoral (immunochemistry)

2.       Review of AI for innate (natural) immunity

C.     Adaptive (acquired) immunity

1.       Acute inflammation

a.     Pathophysiology

1)    Immunohistopathology

2)    Immunochemistry

b.     Hypersensitivity reactions (Type I to IV)

c.     Clinical considerations in acute inflammation

1)    Signs and symptoms

2)    Remove the cause

a)     Hygiene

b)    Anti-infective therapy

c)     Antihistamine/decongestants

d)    Mast cell stabilization

3)       Cold therapy

4)       Palliative therapy

2.   Review of AI for adaptive immunity and acute inflammation

3.   Path to chronic inflammation

 

Chapter Three:  AI and chronic inflammation

A.     Introduction

B.     Pathogenesis of chronic inflammation

1.     Histopathology

2.     Pharmacodynamics

3.  Review of AI for the pathogenesis of chronic inflammation

C.     Clinical diagnosis and treatment

1.    Diagnostic strategies

2.    Treatment (Immunomodulating therapies)

3.    Review of AI for the clinical diagnosis and treatment for chronic inflammation

 

Chapter Four:  AI and autoimmunity

A.      Introduction

B.      Theories of pathogenesis of autoimmune disease

1.     A prolonged inflammatory process;

2.     Failure to eliminate an antigen;

3.     Patient’s genome;

4.     Environmental factors;

5.     Increasing release and accumulation of pro-inflammatory cytokines;

6.     Abnormal immune response to “self”

7.     Review of AI for the theories of autoimmunity pathogenesis

C.    Clinical manifestations of autoimmune disorders

1.     Vascular system

2.     Diffuse organ systems

3.     Review of AI for the clinical manifestations of autoimmune disorders

D.    Autoimmune disease categories

1.    Disease descriptions

2.    Review of AI for autoimmune disease categories

E.    Diagnosis of autoimmune disease

1.     Physical examination

2.     Laboratory

3.     Imaging

4.     Review of AI in the diagnosis of autoimmune disease

F.     Treatment of autoimmune diseases

1.     Medical therapies

2.     Therapeutic procedures

a.     Stem cells transplantation (Regenerative Medicine)

b.     Immunogenetics and Immunogenomics (Molecular biology)

1)       CAR-T Cell (Gene replacement)

2)       CRISPR-Cas9 (Gene editing)

3.    Review of AI in the treatment of autoimmune diseases

 

Chapter Five: AI and immunology considerations in pandemics and SARS-CoV-2 COVID-19

A.   Introduction

B.   Background considerations

1.     Definitions

2.     History of pandemics

a.     Historical overview

b.     Recent history

3.      Incidence and prevalence of COVID-19

B.   Pathogenesis, immunologic and immunogenic considerations for SARS-CoV-2

1.     Mechanisms

2.     Theories

3.     Life cycle of SARS-CoV-2

4.     Review of AI regarding the pathogenesis of SARS-CoV-2 

C.   Clinical considerations for coronavirus (SARS-CoV-2) infection

1.    Clinical manifestations (signs and symptoms)

2.    Diagnostic testing

a.     Antigen testing

b.     Molecular genetic testing (PCR test)

c.     Antibody testing

3.     Treatment and management strategies

a.     General measures

1)       Basic preventive steps

2)       Mitigation

3)       Contact tracing

4)       Modeling

5)       Herd Immunity and R Naught (R0 or R0)

b.     Therapeutics

1)       Monoclonal antibodies

2)       Convalescent plasma (serum)

3)       Hydroxychloroquine (Plaquenilâ) combined with azithromycin (Zithromaxâ)

4)       Remdesivir

5)       Dexamethasone (and corticosteroids)

6)       RNA screening

c.     Vaccines (Immunization)

d.     CRISPR-Cas13 and RNA screening

d.     Immunoinformatics (computational immunology)

4.     Review of AI for clinical considerations for coronavirus infections

D.    Epidemiology and public health considerations in COVID-19

1.     Current epidemiologic considerations

2.     Review of AI  for epidemiology and public health considerations

 

Chapter Six:  Emerging trends and future directions for AI in immunology

A.   The influence of AI and immunology on our personal health and wellness

B.   The influence of AI and immunology on the public health

C.   Current and intermediate considerations of AI applications for immunology

D.   Long range considerations of AI applications for immunology 

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Author(s)

Biography

Dr. Louis J. (“Lou”) Catania is an internationally acclaimed educator, a recognized expert in eye care, health care, AI and disruptive technologies in bioscience. He has authored over 160 journal articles and 9 textbooks including Primary Care of the Anterior Segment from Appleton and Lange which received Baron's Five Star (highest) rating for medical textbooks. He is currently a Senior Clinical Associate with Nicolitz Eye Consultants, a multispecialty ophthalmology group in Jacksonville, FL. He is a lecturer with the University of North Florida, Department of Continuing Education and a visiting Professor at Salus University, College of Health Sciences. During his 52-year clinical and academic career he has taught and lectured extensively worldwide. Over the past 25 years Dr. Catania has expanded his professional scope through postdoctoral studies in immunology, genetics, and artificial intelligence. He has been awarded innumerable honors including 2 Honorary Doctor of Science degrees; named Distinguished Faculty Scholar, State University of New York College of Optometry; inducted into the National Optometry Hall of Fame (2016); Honorary Lecturer at Ohio State University (2017); and commencement speaker and honorary Doctor of Science degree from Salus University (2019).