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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
biology, followed by the formation of a customized and molecular-based method for the administration of anticancer medications. Proper medications for cancerous diseases rely highly on their timely diagnosis for which in vivo molecular imaging technique is popular but a trend for a more feasible approach is seen as molecular imaging requires specialized molecular probes. The use of nanoparticles (NPs) is the current paradigm for diagnosing and treating gastric cancer. With the advent of extensive explorations in the eld of nanotechnology, NPs have been realized to have procient curative properties for gastric cancer. Since the past decade, extensive research work has been allocated to applications of NPs in the direction of therapeutics and diagnosis. Several reports have documented that NPs-based therapeutic agents overcome problems associated with conventional therapy. But, it seems that perusal of the characteristics of NPs and their interactive efcacies with biological entities is vital to analyze the potential of NPs-based nanomedicines and NPs-based diagnostic protocols. Now-a-days green synthesized NPs are also used as a potential agent for gastric cancer treatment. This study is signicant since NPs might also pose certain side effects and toxicity and these aspects should be well addressed prior to the utilization of NPs in biological systems. This chapter will encompass the diverse purview of NPs and how this can be a plausible alternative in the diagnosis and therapeutic treatment of gastric cancer.
Chapter 8
Articial intelligence in hepatitis and chronic liver disease
Akbar Hamid
1
Department of Gastroenterology, Sanjay Gandhi Postgraduate Institute of
Medical Sciences, Lucknow, Uttar Pradesh 226014, India
2
Department of Pharmacology, Heritage Institute of Medical Sciences (HIMS),
Varanasi-221311, India
3
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
1
, Gira Sulabh2and Vinod Kumar3*
University, Varanasi, Uttar Pradesh 221005, India
*Corresponding author (vinodkumarchief@gmail.com)
Articial Intelligence (AI) is a well-developing eld of computer science that imitates human technical thinking to solve problems. The use of different AI models in hepatology is a recent development in the medical eld for better diagnostics. Conventional diagnostic methods are being integrated with modern AI to enhance the performance of treatment. AIs ability to miming the data in human parameters, and forecast the occurrence of hepatitis and other chronic liver diseases. Classifying the different stages of hepatitis, fatty liver disease and hemochromatosis are possible along with the diagnosis and screening. Early disease prediction, complications and mortality can be studied using the algorithms such as regression models, since hepatitis early diagnosis is clinically limited in early stages. AI can predict the risk related to the vascular invasion of hepatocellular carcinoma and hepatitis related to cirrhosis. It also calculates the liver failure rate in HCC patients. Ultimately AI will eventually help in reducing medical errors and managing the patient clinical output.
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
Chapter 9
Articial intelligence applications for clinical decisions support
Bhaskar Sharma Chaturvedi
1
Neurobiology Laboratory, Department of Anatomy, All India Institute of
Medical Sciences, New Delhi 110029, India
2
Systems Toxicology Group, CSIR-Indian Institute of Toxicology Research
3
1*
, Renu Negi2, Anjali Yadav1, Yogesh Sharma1and Vivek K
Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh 201002, India
3
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
University, Varanasi, India
*Corresponding author (sharma.bhaskar003@gmail.com)
Clinical Decision Support (CDS) systems represent a groundbreaking advance­ment in healthcare, fundamentally changing how clinicians make critical decisions by offering evidence-based guidance and knowledge directly at the point of care. By seamlessly integrating with electronic health record (EHR) systems, these platforms harness extensive patient data, medical literature, and best practice guidelines, empowering clinicians with the insights needed for informed decision-making. Through sophisticated analysis of large datasets, CDS systems uncover nuanced patterns and insights that enable early intervention and optimize resource allocation, thereby enhancing patient care outcomes. Despite the transformative potential of CDS, concerns persist regarding algorithm bias, data privacy, and stakeholder engagement, necessitating careful consideration and ongoing renement. Case studies underscore the tangible impact of CDS, demonstrating its ability to enhance adherence to clinical standards, reduce hospital readmissions, and elevate patient satisfaction levels. Furthermore, the integration of articial intelligence (AI) technologies bolsters the capabilities of CDS systems across various domains, including medical imaging analysis, virtual patient care, medication safety assur­ance, diagnostic support, medical research facilitation, and rehabilitation. Administrative applications of AI within CDS systems streamline essential tasks such as claims processing and clinical documentation, driving operational efciency and alleviating administrative burdens on healthcare professionals. In summary, CDS systems play a pivotal role in revolutionizing healthcare delivery by equipping clinicians with actionable insights, improving clinical decision-making, and ulti­mately leading to better patient outcomes.
Chapter 10
Role of articial intelligence in an early diagnosis and prediction of gastric cancer as an advanced therapeutic technique
Juhi Singh
1
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
1
and Vinod Kumar Dixit
1*
University, Varanasi 221005, India
*Corresponding author (drvkdixit@gmail.com, vkdixit@bhu.ac.in) (Phone number:
8601100564)
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
One of the most prevalent malignant tumours with a high fatality rate is gastric cancer (GC). Human professionalsmeticulous assessments of medical pictures are crucial for making accurate diagnoses and treatment choices for GC. This ailment has historically proven difcult to diagnose. Furthermore, the imaging settings, limited expertise, objective criteria, and inter-observer inconsistencies impede the development of accuracy. Healthcare research has advanced thanks to articial intelligence (AI). Applications that help with cancer diagnosis and prognosis have been developed as a result of the accessibility of open-source healthcare statistics. Accurate evaluation, diagnosis, and treatment of stomach malignant growth and helicobacter pylori bacteria can be achieved with AI-assisted image analysis; links between these sub-elds can give more information than traditional analysis. AI­assisted categorization of genomic, epigenetic, and metagenomic data may lead to improved personalised therapy recommendations for gastrointestinal malignancies. In a number of therapeutic settings, including GC, researchers are looking at the extensive uses of articial intelligence (AI). With endoscopic inspection and pathologic evidence during GC screening, AI can identify precancerous conditions and help with early cancer identication. AI can help TNM staging and subtype categorization in the diagnosis of GC. AI can assist with prognosis prediction and surgical margin estimation for treatment options. Here, we include some AI methods for early stomach cancer prediction. Even though several methods advocated in various texts have shown excellent prediction outcomes, cancer mortality has not decreased. As a result, a further in-depth study is needed in the eld of cancer prediction in relation to AI that may be applied as a therapy.
Chapter 11
Nanomedicines in liver brosis
Saras Tiwari Vivek K Chaturvedi
1
Department of Cellular and Molecular Medicine, Faculty of Medicine,
University of Ottawa, Canada
2
Neurobiology Laboratory, Department of Anatomy, All India Institute of
Medical Sciences, New Delhi 110029, India
3
State University of New York Upstate Medical University, USA
4
Electron Microscopy Facility, All India Institute of Medical Sciences, New
Delhi 110029, India
5
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
1
, Bhaskar Sharma2, Jugasmita Deka3, Prabhakar Singh4*and
5
University, Varanasi, India
*Corresponding author (prabhakar.singh@aiims.edu)
Chronic infection of liver cells causes scarring on liver tissue, resulting in Liver Fibrosis (LF), which is now a major global health concern. Hepatitis C, Hepatitis B, and alcohol abuse are the leading causes of liver damage, which results in the deposition of Extracellular cell matrix (ECM) and liver brosis. Ultrasonography and magnetic resonance imaging are commonly used as non-invasive diagnostic methods for hepatic brosis. The conventional therapy used to treat liver diseases is
xxxii
Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
ineffective because it does not deliver a sufcient amount of drug concentration in the liver and is imprecise. Several clinical and preclinical Study has shown that the utilisation of nanotechnology to deliver therapeutic agents including drug molecules, and nucleic acids, in adequate amount and to target specically the HSC (hepatic stellate cells) could be the future treatment to cure Liver diseases caused by LF. According to research, nanomedicines can reverse premature hepatic brosis. Many nanoparticulate systems (NPs) such as Liposomes, Inorganic NPs, and Nano-micelles have been studied because of their diverse properties for drug delivery and in addition to some therapeutic moieties. Out of these, Liposomal NPs have shown very promising results in clinical trials and are being considered as an extremity for the treatment of hepatic brosis. This book chapter discusses the causes, pathogenesis, diagnosis, and nanoparticulate systems used in the treatment of chronic liver diseases.
Chapter 12
Articial intelligence (AI) based colonoscopy
Akbar Hamid Gira Sulabh
1
Department of Hepatology, Sanjay Gandhi Post Graduate Institute of Medical
Sciences, Lucknow, India
2
Maharaja Agrasen School of Pharmacy, Maharaja Agrasen University, Atal
Shiksha Kunj, Solan, Himachal Pradesh, India
3
Department of Pharmacology, Heritage Institute of Medical Sciences (HIMS),
Varanasi-221311, India
4
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
1#
3
, Vinod Kumar4* and D P Yadav4*
, Rajesh Kumar2#, Vivek K Chaturvedi3, Sunil Dutt2,
University, Varanasi, India
#Sharing co-rst author
*Corresponding author (vinodkumarchief@gmail.com; devesh.thedoc@gmail.com)
With the increase in the world population and development, a number of health­related issues are also increasing in gastrology. One of the major causes is poor food habits. To deal with this constant advancement is required in the eld of medical sector which will not only help in easy and earlier diagnosis of the underlying health issue but also in accurate diagnosis. In this chapter advancement and collaboration of articial intelligence with the medical sector are discussed below. How one technique helps is the accurate detection of colorectal cancer as well as other disease such as IBD or any other abnormalities in the colon. A different version of colonoscopy has been developed along with articial intelligence discussed in this chapter with the future aspect and advancement.
xxxiii

List of contributors

Zeba Azim
Department of Botany, University of Allahabad, Prayagraj 211002, India
Bharmjeet
Department of Biotechnology, Delhi Technological University, New Delhi
110042, India
Prakash Chandra
Department of Biotechnology, Delhi Technological University, New Delhi
110042, India
Vivek K Chaturvedi
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
University, Varanasi, Uttar Pradesh 221005, India
Asmita Das
Department of Biotechnology, Delhi Technological University, New Delhi
110042, India
Jugasmita Deka
State University of New York Upstate Medical University, USA
Vinod Kumar Dixit
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
University, Varanasi 221005, India
Sunil Dutt
Maharaja Agrasen School of Pharmacy, Maharaja Agrasen University, Atal
Shiksha Kunj, Solan, Himachal Pradesh 174103, India
Niraj Kumar Goswami
Mahant Avaidyanath Government Degree College, Jungle Kaudia, Gorakhpur,
India
Ankush Goyal
Maharaja Agrasen School of Pharmacy, Maharaja Agrasen University, Atal
Shiksha Kunj, Solan, Himachal Pradesh 174103, India
Rahul Gupta
Department of Information Technology, Delhi Technological University, New
Delhi 110042, India
Akbar Hamid
Department of Hepatology, Sanjay Gandhi Postgraduate Institute of Medical
Sciences, Lucknow, Uttar Pradesh 226014, India
xxxiv
Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
Mazharul Haque
School of Biological Sciences, CNBR, Alabama State University, USA
Ashutosh Kumar
Department of Ophthalmology, University of California Los Angeles, California-
90095, USA
Brijesh Kumar
Department of Pharmacology, Institute of Medical Sciences, Banaras Hindu
University, Varanasi 221005, India
Rajesh Kumar
Maharaja Agrasen School of Pharmacy, Maharaja Agrasen University, Atal
Shiksha Kunj, Solan, Himachal Pradesh 174103, India
Vinod Kumar
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
University, Varanasi, Uttar Pradesh 221005, India
Renu Negi
Systems Toxicology Group, CSIR-Indian Institute of Toxicology Research
Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, Academy of
Scientic and Innovative Research (AcSIR), Ghaziabad, Uttar Pradesh 201002,
India
Nida-e-Falak
Department of Biotechnology, Delhi Technological University, New Delhi
110042, India
Ritu
Department of Biotechnology, Delhi Technological University, New Delhi
110042, India
Bhaskar Sharma
Neurobiology Laboratory, Department of Anatomy, All India Institute of
Medical Sciences, New Delhi 110029, India
Yogesh Sharma
Neurobiology Laboratory, Department of Anatomy, All India Institute of
Medical Sciences, New Delhi 110029, India
Anshu Singh
Department of Chemistry, Institute of Science, Banaras Hindu University,
Varanasi 221005, India
Anurag K Singh
Department of Pharmaceutical Engineering and Technology-Indian Institute of
Technology, BHU, Varanasi, India
xxxv
Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
Cancer Biology Research and Training, Department of Biological Sciences,
Alabama State University, 915 S Jackson Street, Montgomery AL 361010271,
USA
Jay Singh
Department of Chemistry, Institute of Science, Banaras Hindu University,
Varanasi 221005, India
Juhi Singh
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
University, Varanasi 221005, India
Kshitij R B Singh
Graduate School of Life Science and Systems Engineering, Kyushu Institute of
Technology, Kitakyushu, Japan
Prabhakar Singh
Electron Microscopy Facility, All India Institute of Medical Sciences, New Delhi
110029, India
Pratistha Singh
Department of Ophthalmology, University of California Los Angeles, California
90095, USA
Shefali Singh
Department of Botany, Kashi Naresh Government Post Graduate, College,
Gyanpur, Bhadohi, U.P. 221304, India
Gira Sulabh
Department of Pharmacology, Heritage Institute of Medical Sciences (HIMS),
Varanasi-221311, India
Saras Tiwari
Department of Cellular and Molecular Medicine, Faculty of Medicine,
University of Ottawa, Canada
Komal Vig
School of Biological Sciences, CNBR, Alabama State University, USA
Anjali Yadav
Neurobiology Laboratory, Department of Anatomy, All India Institute of
Medical Sciences, New Delhi 110029, India
Dawesh P Yadav
Department of Gastroenterology, Institute of Medical Sciences, Banaras Hindu
University, Varanasi 221005, India
Navneet Yadav
Department of Mechanical Engineering, Faculty of Science and Engineering,
Swansea University, Swansea SA1 8EN, United Kingdom
xxxvi
Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
Ravi Kumar Yadav
Department of Botany, Kashi Naresh Government Post Graduate, College,
Gyanpur, Bhadohi, U.P. 221304, India
Mohammad Zafaryab
School of Biological Sciences, CNBR, Alabama State University, USA
xxxvii

Introduction

Nanotechnology and articial intelligence (AI) have the potential to transform the existing treatment and diagnosis choices for gastrointestinal (GI) disorders. Several studies have shown that GI diseases can be early diagnosed and successfully treated using nanomaterials associated with AI applications. The GI tract has become a considerable target system for nanotechnology and AI, and it contains a wide range of substances, such as water, nutrients, or therapeutics that are absorbed in the GI tract when transported through the digestive tract. The behaviour of nanotechnol­ogy employed for GI disease diagnosis or therapy can be controlled depending on the pH, pressure, transit duration, and bacterial concentration of each specic nanomaterial. Because of their adjustable interactions with macrophages, M cells, immune cells and intestinal epithelial cells nanoparticles have demonstrated con­siderable promise in gastroenterology and may become a potential delivery system for vaccines. The use of AI-based advanced machines for GI surgery as well as in the study of medicine is expanding quickly. AI within the diagnostic process supports medical specialists to improve the level of diagnostic accuracy and efciency, thus providing emergent digitalized healthcare services. Nanotechnology with AI is anticipated to have a signicant impact on how GI disorders are diagnosed and treated. In terms of effectiveness, dependability, and practicality, several of the medicines and diagnostics based on AI described here outperform traditional materials. In the future, GI problems may be successfully treated using AI-based machines and their intricate mixes, which may include therapeutic substances. This book explains how the most recent advances in applications of novel biomaterials, nanotechnology and AI have paved the way for breakthroughs in drug delivery. This book demonstrates present and future applications in a setting where it is essential to provide effective, patient-centered, and long-lasting healthcare systems. This book provides an overview of the technological approaches mainly focused on the role of AI and their implications in GI disorders such as abdominal pain, bowel obstruc­tion, diarrhoea, pancreatitis, upper gastrointestinal bleeding (UGIB), non-alcoholic fatty liver diseases (NAFLD), intestinal tuberculosis (ITB), celiac disease, and duodenal ulcer as well as include the role of nanotechnology and AI in GI illnesses. Due to its high calibre material, the book will appeal to a wide range of readers, including academics, students, researchers and medical students as well as practi­tioners. It would be particularly interesting to readers interested in health, business, and research linked to the biomedical sciences. The main marketing and differ­entiating factors are the numerous libraries operating in numerous reputable private and governmental institutions or organizations.
xxxviii
IOP Publishing
Nanobiotechnology and Artificial Intelligence in
Gastrointestinal Diseases
Vivek K Chaturvedi, Anurag Kumar Singh, Jay Singh and Dawesh P Yadav
Chapter 1
Nanotechnology and artificial intelligence
Anshu Singh, Vivek K Chaturvedi, Anurag K Singh, Jay Singh, Kshitij R B Singh and
Dawesh P Yadav
The convergence of nanotechnology and articial intelligence (AI) in medical science heralds a transformative era, promising groundbreaking innovations in diagnostics, therapeutics, and personalized medicine. Nanotechnology, operating at the scale of individual atoms and molecules, facilitates the design of advanced materials with unique properties, enabling precise drug delivery, diagnostic imaging, and theranostics. On the other hand, AI, with its prowess in machine learning (ML) and data analysis, enhances medical decision-making, diagnostic accuracy, and patient care. This chapter explores the revolutionary synergy between nanotechnol­ogy and AI, examining their individual contributions and the synergistic effects when integrated. In the realm of nanotechnology, the utilization of nanomaterials for drug delivery systems is explored, showcasing their ability to enhance targeting, reduce side effects, and revolutionize treatment, with a particular focus on successful applications in cancer therapy. Additionally, the development of nanosensors for diagnostics is discussed, emphasizing their role in early disease detection, real-time monitoring, and imaging.

1.1 Introduction

The convergence of nanotechnology and AI in the eld of medical science marks a paradigm shift that holds the promise of revolutionizing healthcare on an unprece­dented scale. This groundbreaking synergy combines the precision and versatility of nanoscale technologies with the analytical prowess of intelligent algorithms, paving the way for transformative advancements in diagnostics, treatment modalities, and overall patient care. Nanotechnology, operating at the scale of individual atoms and molecules, allows for the precise engineering of materials and devices with novel properties. This capability has given rise to a myriad of applications, ranging from
doi:10.1088/978-0-7503-6134-7ch1 1-1 ª IOP Publishing Ltd 2024