Artificial Intelligence Technologies in Healthcare: Diagnosis, Intervention and Ethical Integration | Book Publisher International

 

The rapid advancement of Artificial Intelligence (AI) technologies has initiated a paradigm shift in healthcare, particularly in the realms of medical diagnosis and treatment. This study provides a comprehensive academic examination of how AI, through subfields such as machine learning, deep learning, and natural language processing, is revolutionising clinical decision-making, diagnostic precision, and individualised patient care. The work systematically explores AI's integration into key healthcare domains, including medical imaging, predictive analytics, personalised medicine, and robotic surgery. Specific attention is given to the application of convolutional neural networks (CNNs) in radiology, pathology, and dermatology, where AI systems now rival human experts in diagnostic accuracy.

 

Furthermore, this research highlights the predictive power of AI in identifying the onset of chronic and neurodegenerative diseases by leveraging electronic health records (EHRs), genomic data, and wearable technologies. In personalised medicine, AI facilitates pharmacogenomic profiling and individualised oncology treatment strategies. The integration of AI in surgical robotics is also examined, emphasising improvements in intraoperative precision and post-operative monitoring.

 

While the potential of AI is vast, the study also addresses significant challenges, including data privacy, algorithmic bias, lack of transparency, and regulatory hurdles. Ethical and legal considerations are critically analyzed, underscoring the need for fair, interpretable, and accountable AI systems. The final chapters focus on future directions, such as multimodal data integration, explainable AI (XAI), federated learning, and human-AI collaboration, which are poised to shape the next generation of healthcare solutions.

 

This research concludes with policy recommendations and strategic priorities to guide responsible AI deployment in clinical environments, advocating for interdisciplinary collaboration and robust governance frameworks. The findings underscore AI’s transformative potential in medicine, while emphasizing the importance of ethical oversight and equity in technological advancement.

 

 

Author(s) Details

Dr. Rooth Vasantha Medapati
Human Genetics Department, Andhra University, Visakhapatnam, Andhra Pradesh, India.

 

Dr. V.Raja Babu
Sun Institute of Paramedical Sciences, Pendurthi, Visakhapatnam, Andhra Pradesh, India.

 

Prof. Saritha Medapati
Vignan Institute of Pharmaceutical Technology, Duvvada, Visakhapatnam, Andhra Pradesh, India.

 

Dr. D.Udaya Kumar
Human Genetics Department, Andhra University, Visakhapatnam, Andhra Pradesh, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-81-989371-9-3

Homeogenomics: Unraveling Genetic Regulation and Therapeutic Potential | Chapter 4 | Medical Science: Trends and Innovations Vol. 11

Homeogenomics primarily focuses on understanding the interactions between homoeopathic remedies and the genetic blueprint or genome. This involves the identification of which gene or genes are targeted by a particular remedy. A new area of research has been raised to explore the possibility of developing a personalized remedy selection procedure by application of molecular homeogenomics. The application of personalized medicine in medical practice requires the study of the human genome with regard to drug pharmacokinetics, pharmacodynamics, interactions and tolerance profile. The consideration of gene × environment interactions and the inclusion of “omics’ ‘data in pharmacogenomic studies of drugs will facilitate the generation of reliable results and will promote tailored treatments and new strategies of research and development. Pharmacogenetics is the search for genetic polymorphisms that affect responses to drug therapy and refers to the study of variations in a single gene, whereas pharmacogenomics is the study of variations in multiple genes and the basis of personalisation of treatment to allow higher medication success rates.

This study proposes a philosophical–scientific correlation between homeopathic remedıes and epigenetic modifications as homeopathic medicine being also a modulator of gene expression.

Based on the study of homeopathic doctrine and epigenetics, a conceptual and functional correlation is observed between homeopathic remedies and epigenetic modifications. Homeopathic remedies act on the Genome by modulating gene expression.  Several experimental studies suggest that homeopathy’s mechanism of action may be by modulating gene expression.

According to modern genetics, epigenetic alterations are the fundamental cause of the manifestation of chronic diseases as well as therapeutic modulator of gene expression for their management. Homeopathıc remedies may act on the epigenetic expression of the individual to heal personally and holistically.

 

Author (s) Details

Cengiz Mordeniz
Department of Anesthesiology and Intensive Care, Medical Faculty, Tekirdag Namik Kemal University, Turkey.

 

Please see the book here:- https://doi.org/10.9734/bpi/msti/v11/4653

Next-Generation Drug Delivery Strategies for Personalized Healthcare | Chapter 3 | Pharmaceutical Research - Recent Advances and Trends Vol. 2

 

The advent of personalized medicine has revolutionized healthcare, allowing tailored treatment plans based on individual patient characteristics. Central to this paradigm shift are advanced drug delivery strategies designed to enhance therapeutic efficacy, minimize side effects, and improve patient outcomes. This review paper provides a comprehensive overview of next-generation drug delivery approaches, focusing on their application in personalized healthcare. We discuss various strategies, including nanomedicine, targeted drug delivery systems, stimuli-responsive delivery systems, and biomaterial-based platforms, highlighting their potential to address the challenges of conventional drug administration methods. Furthermore, we examine the integration of personalized diagnostics and therapeutics, emphasizing the importance of precision medicine in optimizing treatment regimens for individual patients. Overall, this review underscores the critical role of innovative drug delivery technologies in advancing personalized healthcare and shaping the future of medicine.

 

Author(s)details:-

 

Shubham Shende
Manwatkar College of Pharmacy, Ghodpeth, Tah. Bhadravati, Dist. Chandrapur- - 442902, MH., India and Department of Pharmaceutical Science, Sage University, Indore-452020, MP, India.

 

Lalchand Devhare
Manwatkar College of Pharmacy, Ghodpeth, Tah. Bhadravati, Dist. Chandrapur- - 442902, MH., India.

 

Chandani Prasad
Manwatkar College of Pharmacy, Ghodpeth, Tah. Bhadravati, Dist. Chandrapur- - 442902, MH., India.

 

Ashish Khobragade
Manwatkar College of Pharmacy, Ghodpeth, Tah. Bhadravati, Dist. Chandrapur- - 442902, MH., India.

 

Ajit Khapne
Department of Pharmaceutical Science, Sage University, Indore-452020, MP, India.

 

Please See the book here :- https://doi.org/10.9734/bpi/prrat/v2/275

AI in Pharmaceutical Manufacturing: Present Senario in Pharma Industry | Chapter 6 | Pharmaceutical Research - Recent Advances and Trends Vol. 1

 

Artificial intelligence (AI) is becoming a potential model that uses human knowledge to solve difficult problems more quickly. The field of drug discovery, pharmaceutical formulation, and dosage form testing is about to undergo a radical change because of remarkable developments in AI and machine learning. Researchers may find disease-associated targets and anticipate how they would interact with possible treatment options by using AI-developed programs that examine vast biological data like proteomics and genomics. This raises the likelihood of successful pharmaceutical approvals by allowing for an efficientive and concentrated approach to drug development. AI may also save development costs by streamlining the research and development process. AI models enable pharmaceutical companies to design, automate, evaluate, and monitor human-centric and integration-centric activities and processes, helping them to deliver novel medicines more cost-effectively and on time. It improves repeatability, control, and visibility inside the firm while also streamlining and simplifying operations. It may help pharmaceutical manufacturers quickly understand and implement procedures and systems to improve their company operations, offering them the agility they require to respond to changing situations, new legislation, and expectations for a short product delivery life-cycle. Artificial intelligence evaluates patient information and enables the personalization of medicine approaches, hence improving patient adherence and treatment outcomes. This thorough overview section delves into the many uses of AI in the creation of drug delivery, formulation development, process optimization, evaluation, and PK/PD studies. The article discusses the benefits and drawbacks of several AI model strategies applying in pharmaceutical manufacturing. However, the pharmaceutical industry's increasing research and investment in AI creates several prospects for enhancing the treatment of patients and drug development processes.

 

Author(s) Details:

 

Dr. Kotha Kranthi Kumar (Associate Professor)
Department of Pharmaceutics, College of Pharmaceutical Sciences, Dayananda Sagar University, Bengaluru, Karnataka, India.

 

Mrs. Jyothi M. (Associate Professor)
Department of Pharmaceutics, East Point College of Pharmacy, East Point Group of Institutions, Jnana Prabha, East Point Campus, Virgo Nagar, Bidarahalli, Karnataka, India.

 

Please see the book here:  https://doi.org/10.9734/bpi/prrat/v1/194

The Application of 3-D Printing in Nanomedicine | Chapter 13 | Advanced Concepts in Pharmaceutical Research Vol. 9

 

The most cutting-edge method for producing pharmaceutical dosage forms in recent years has been 3D printing or additive manufacturing. This approach uses advanced technology, like a virtual model, to control the production apparatus and produce the desired dosage form of an actual object. Due to the demand from different sectors of the world for health services and the urgency of controlling the side effects associated with conventional dosage forms, the pharmaceutical industry tries to produce dosage forms in large quantities these days with 3D printing. With this technology, items are designed through layer-by-layer material manufacturing employing layer-based systems of processes, extrusion, ink-jet printing, and laser printing technologies by using various polymers and other suitable excipients. Additionally, the various delivery systems, such as customized drug doses and personalized medicine, as well as other healthcare sectors, demonstrate the potential benefits of 3D technology in delivering personalized therapy to the individual. This overview covers the various methods and how they are used in the production of 3D medicines, as well as the regulatory issues that this industry faces.

Author(s) Details:

Nirmala Rani Tulimelli
Department of Pharmaceutical Technology, College of Pharmaceutical Sciences, Andhra University. Visakhapatnam-530003, India.

Shailaja Pashikanti
Department of Pharmaceutical Technology, College of Pharmaceutical Sciences, Andhra University. Visakhapatnam-530003, India.

Rajeswari Athota
Department of Pharmaceutical Technology, College of Pharmaceutical Sciences, Andhra University. Visakhapatnam-530003, India.

Naga Narayana Lakshmi. P
Department of Pharmaceutical Regulatory Affairs, College of Pharmaceutical Sciences, Andhra University. Visakhapatnam-530003, India.

Please see the link here: https://stm.bookpi.org/ACPR-V9/article/view/14379

Artificial Intelligence (AI) and Its Application in Pharmacy | Chapter 12 | Advances and Challenges in Science and Technology Vol. 9

 The AI is an active tool for data excavating based on the gigantic pharmacological data and machine learning process. Therefore, AI has been used in again drug design, activity scoring, in essence screening and in silico judgment in the properties (absorption, classification, metabolism, excretion and toxicity) of a drug particle. AI has made important contributions to the healthcare industry in any of areas, including the administration and storage of data and news about patient medical histories, cure stocks, sale records, and more; automated appliance; software and computer uses; and diagnostic finishes like CT and MRI diagnostics. All of these have been grown to support and streamline healthcare procedures. As expected, artificial intelligence (AI) has transformed healthcare expected more effective and adept, and the pharmaceutical industry is not exempt. All along the past few years, a substantial amount of increasing interest in the uses of AI science has been identified for resolving as well as interpreting few important fields of pharmacy like drug finding, dosage form crafty, poly pharmacology, and hospital pharmacy. AI-located solutions have been labeled which involve platforms that can make use of a difference of data types viz. manifestations reported for one patients, biometrics, imaging, biomarkers, etc. We engaged to produce a thorough report that would aid every undertaking pharmacist in understanding the major progresses made likely by the application of machine intelligence (AI), in light of the field's expanding meaning. In order to conclude the outbreaks of COVID-19, Zika, Ebola, and seasonal influenza, deep education and neural networks were utilized. Accompanying the advancement of AI technologies, the experimental community concede possibility witness rapid and cost-effective healthcare and drug research as well as provide upgraded service to the society.

Author(s) Details:

R. Radha,
Department of Pharmaceutical Chemistry, Seven Hills College of Pharmacy (Autonomous), Tirupati, India.

V. Neelima,
Department of Pharmaceutical Chemistry, Seven Hills College of Pharmacy (Autonomous), Tirupati, India.

M. P. VedaVarshan,
Department of Pharmaceutical Chemistry, Seven Hills College of Pharmacy (Autonomous), Tirupati, India.

S. Saqib Basha,
Department of Pharmaceutical Chemistry, Seven Hills College of Pharmacy (Autonomous), Tirupati, India.

U. Jeevitha,
Department of Pharmaceutical Chemistry, Seven Hills College of Pharmacy (Autonomous), Tirupati, India.

M. A. KapilKumar,
Department of Pharmaceutical Chemistry, Seven Hills College of Pharmacy (Autonomous), Tirupati, India.

G. Sateesh Kumar,
Department of Pharmaceutical Chemistry, Seven Hills College of Pharmacy (Autonomous), Tirupati, India.

Please see the link here: https://stm.bookpi.org/ACST-V9/article/view/12634

A Brief Study about Choriocapillaris Vascular Density Changes: Healthy Vs. Advanced Exudative Age-related Macular Degeneration Previously Treated with Multiple Anti-VEGF Intravitreal Injections | Chapter 14 | New Horizons in Medicine and Medical Research Vol. 5

 The goal of this study was to use OCT-A to emphasise the differences in choriocapillaris VD in healthy ae-AMD eyes.

Introduction: Since the implementation of OCT-A in clinical practise, we have made significant progress in our understanding of age-related macular degeneration, particularly the exudative variety (AMD).

Method: In this observational, cross-sectional investigation, 21 healthy and 21 ae-AMD eyes were included, all of which had already been treated with anti-VEGF. All subjects had their Angio-View retina patterns focused on the fovea (6.4 mm) recorded using a Solix full-range OCT (Optovue Inc., Freemont, CA, USA). The primary goal of the study was to examine choriocapillaris VD in healthy and ae-AMD eyes. For the analysis, automated measurements of whole image choriocapillaris VD (percent) and fovea grid-based (percent) were taken. The contour flow measure algorithm was utilised to assess the flow area (mm2) of macular neovascularization (MNV) using Angio-View patterns. The statistical analysis included both groups' best-corrected visual acuity (BCVA).

The average age in healthy eyes was 60.9 (8.3), but in ae-AMD eyes it was 73.33 (15.05). The mean BCVA (ETDRS letters) in healthy eyes was 98.47 (1.50) and 7.04 (5.96) in ae-AMD eyes. The Mann–Whitney test revealed statistical significance when comparing choriocapillaries VD for entire and fovea healthy and ae-AMD eyes (p 0.0001 (t = 4.91; df = 40) and p 0.0001 (t = 6.84; df = 40), respectively). The link between MNV and VD of choriocapillaries was not statistically significant in either the entire or fovea areas (F = 0.38 (R2 = 0.01) and 1.68 (R2 = 0.08), respectively). Furthermore, type 3 MNV was found to have higher choriocapillaris non-perfusion in this investigation. The choriocapillaris is particularly fascinating to research when it comes to the pathogenesis of type 3 MNV.

Conclusions: In ae-AMD eyes, choriocapillaris VD was statistically significantly lower than in healthy eyes. In the early stages of MNV pathogenesis, choriocapillaris dysfunction might be noticed. Future applications could be used to assess choriocapillaris VD in a variety of MNVs, including Type 1, Type 2, Combined Type 1–Type 2, RAP, and polypoidal choroidal vasculopathy (PCV).

Author(S) Details

Maria Cristina Savastano
Unit of Ophthalmology, Fondazione Policlinico A. Gemelli, IRCCS, 00191 Rome, Italy and Unit of Ophthalmology, Università Cattolica Sacro Cuore, 00168 Rome, Italy.

Clara Rizzo
Ophthalmology, Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, 56126 Pisa, Italy.

Gloria Gambini
Unit of Ophthalmology, Fondazione Policlinico A. Gemelli, IRCCS, 00191 Rome, Italy and Unit of Ophthalmology, Università Cattolica Sacro Cuore, 00168 Rome, Italy.

Alfonso Savastano
Unit of Ophthalmology, Fondazione Policlinico A. Gemelli, IRCCS, 00191 Rome, Italy and Unit of Ophthalmology, Università Cattolica Sacro Cuore, 00168 Rome, Italy.

Benedetto Falsini
Unit of Ophthalmology, Fondazione Policlinico A. Gemelli, IRCCS, 00191 Rome, Italy and Unit of Ophthalmology, Università Cattolica Sacro Cuore, 00168 Rome, Italy.

Daniela Bacherini
Department of Surgery and Translational Medicine, AOU Careggi, University of Florence, 50139 Florence, Italy.

Carmela Grazia Caputo
Unit of Ophthalmology, Fondazione Policlinico A. Gemelli, IRCCS, 00191 Rome, Italy and Unit of Ophthalmology, Università Cattolica Sacro Cuore, 00168 Rome, Italy.

Raphael Kilian
Ophthalmology Unit, University of Verona, 37134 Verona, Italy.

Francesco Faraldi
Torino, Eye Clinic, ASL Torino 5, 10024 Turin, Italy.

Umberto De Vico
Unit of Ophthalmology, Fondazione Policlinico A. Gemelli, IRCCS, 00191 Rome, Italy

Stanislao Rizzo
Unit of Ophthalmology, Fondazione Policlinico A. Gemelli, IRCCS, 00191 Rome, Italy and Unit of Ophthalmology, Università Cattolica Sacro Cuore, 00168 Rome, Italy and Consiglio Nazionale della Ricerca (CNR), Istituto di Neuroscienze, 56124 Pisa, Italy.


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Study on the Role of ABCB1 and Glutathione S-transferase Gene Variants in the Association of Porphyria Cutanea Tarda and Human Immunodeficiency Virus Infection | Chapter 21 | New Frontiers in Medicine and Medical Research Vol. 4

 Porphyrias are a series of metabolic diseases caused by problems with heme production. Porphyria Cutanea Tarda (PCT) is a hepatic cutaneous Porphyria caused by a defect in Uroporphyrinogen decarboxylase, which can be acquired or inherited. The onset of this disease is influenced by triggering circumstances. In Argentina, PCT is highly linked to HIV infection; however, it is unknown whether the development of the disease is linked to HIV infection and/or antiretroviral therapy. The goal of our research was to look into the role of genetic variations in the development of Porphyrias. The goal of this study was to see if ABCB1 and GST genetic variations played a role in the link between PCT and HIV. The important reports on the role of drug metabolism in the start of PCT, particularly those involving cytochrome P-450 gene variations, were summarised in this article. Furthermore, we detailed our findings on the role of ABCB1 transporter and Glutathione S-transferases (GSTs) variations in the PCT-HIV association. Exon 12 (rs1128503, NM 000927.5: c.1236C>T), exon 21 (rs2032582, NM 000927.5: and c.2677G>T/A), and exon 26 (rs1045642, NM 000927.5: and c.3435C>T) are all ABCB1 gene variations that alter drug efflux. GSTT1 null, GSTM1 null, and GSTP1 (rs1695, NM 000852.4: and c.313A>G), gene variants that alter activity and modify xenobiotic levels, were genotyped. The high prevalence of c.3435C>T (PCT and PCT-HIV) and c.1236C>T (PCT) suggested that the beginning of PCT for these variations was unrelated to HIV infection or antiretroviral therapy. The frequency of c.2677G>T/A in PCT-HIV patients was higher than in the other groups, suggesting that antiretroviral treatment played a role in this connection. GSTT1 null variants were similarly common in PCT-HIV patients, although GSTM1 null variants were uncommon. A combination of the absence of GSTT1 and the presence of GSTM1 could represent the genetic basis for PCT onset. PCT-HIV patients had greater risk alleles than Controls, PCT, or HIV groups when all gene variants were considered. Finally, genes encoding proteins involved in the flow and metabolism of xenobiotics may influence the PCT-HIV relationship, revealing new information on the molecular basis of the PCT-HIV relationship.

Author (S) Details

Priscila Ayelén Pagnotta
Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, 1428 Buenos Aires, Argentina and Laboratorio de Química de Proteoglicanos y Matriz Extracelular, Instituto de Biología y Medicina Experimental (IBYME), 1428 Buenos Aires, Argentina.

Viviana Alicia Melito
Departamento de Química Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, 1428 Buenos Aires, Argentina and Centro de Investigaciones sobre Porfirinas y Porfirias, Universidad de Buenos Aires, Argentina-Consejo Nacional de Investigaciones Científicas y Técnicas, Hospital de Clínicas José de San Martín, 1120, Buenos Aires, Argentina.

Jimena Verónica Lavandera
Cátedra de Bromatología y Nutrición, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral, 3000, Santa Fe, Argentina.

María Laura Buscalia
Centro de Investigaciones sobre Porfirinas y Porfirias, Universidad de Buenos Aires, Argentina-Consejo Nacional de Investigaciones Científicas y Técnicas, Hospital de Clínicas José de San Martín, 1120, Buenos Aires, Argentina.

Victoria Estela Parera
Centro de Investigaciones sobre Porfirinas y Porfirias, Universidad de Buenos Aires, Argentina-Consejo Nacional de Investigaciones Científicas y Técnicas, Hospital de Clínicas José de San Martín, 1120, Buenos Aires, Argentina.

María Victoria Rossetti
Centro de Investigaciones sobre Porfirinas y Porfirias, Universidad de Buenos Aires, Argentina-Consejo Nacional de Investigaciones Científicas y Técnicas, Hospital de Clínicas José de San Martín, 1120, Buenos Aires, Argentina.

Johanna Romina Zuccoli
Centro de Investigaciones sobre Porfirinas y Porfirias, Universidad de Buenos Aires, Argentina-Consejo Nacional de Investigaciones Científicas y Técnicas, Hospital de Clínicas José de San Martín, 1120, Buenos Aires, Argentina.

Ana Maria Buzaleh
Laboratorio de Química de Proteoglicanos y Matriz Extracelular, Instituto de Biología y Medicina Experimental (IBYME), 1428 Buenos Aires, Argentina and Centro de Investigaciones sobre Porfirinas y Porfirias, Universidad de Buenos Aires, Argentina-Consejo Nacional de Investigaciones Científicas y Técnicas, Hospital de Clínicas José de San Martín, 1120, Buenos Aires, Argentina.

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A Current and Evolving Treatment Landscape on Esophageal Cancer | Chapter 16 | Highlights on Medicine and Medical Research Vol. 10

 Overall survival for patients with many types of tumours has improved thanks to developments in cutting-edge technology, trendy diagnostic and prognostic molecular markers, and cutting-edge surgical procedures. However, there is a gap between esophageal cancer and the rapid advancements in cancer treatment found in other cancers. The 5-year survival rate for patients with esophageal cancer is just 19.9%, according to statistics from the Surveillance, Epidemiology, and End Results Program (SEER) [1]. Poor prognosis is most likely attributable to an overabundance of patients with advanced disease at the time of diagnosis, as well as the disappointing results of present treatments. The epidemiology and recently revised staging of esophageal and esophagogastric junction tumours will be discussed in this article. Endoscopic resection, surgery, radiation therapy, and systemic therapy will be discussed individually and as components of multimodality treatment. We'll go over how targeted therapy and immunotherapy have changed the treatment environment. Clinical research is shifting away from classic empiric chemotherapy and toward more customised treatments based on molecular oncology and immunotherapy. Further research into prognostic values may aid in determining the best treatment and management strategy for patients with esophageal cancer, with the goal of improving survival. Lessons obtained in epidemiology, molecular genetics, pharmacogenomics, and precision medicine are used to inform clinical trials examining prevention, early diagnosis, and therapy of early and advanced disease.

Author(s) Details

Nicole B. Balmaceda
University of Kansas School of Medicine, University of Kansas, 3901 Rainbow Blvd, Kansas City, Kansas 66160, USA.

Joaquina C. Baranda
Department of Hematology and Medical Oncology, University of Kansas Cancer Center, 2330 Shawnee Mission Parkway, Westwood, KS 66205, USA.

Peter DiPasco
Department of Surgery, University of Kansas, 3901 Rainbow Blvd, Kansas City, Kansas 66160, USA.

Weijing Sun
Department of Hematology and Medical Oncology, University of Kansas Cancer Center, 2330 Shawnee Mission Parkway, Westwood, KS 66205, USA.

John Ashcraft
Department of Hematology and Medical Oncology, University of Kansas Cancer Center, 2330 Shawnee Mission Parkway, Westwood, KS 66205, USA.

Joseph Valentino
Department of Hematology and Medical Oncology, University of Kansas Cancer Center, 2330 Shawnee Mission Parkway, Westwood, KS 66205, USA.

Mazin Al-Kasspooles
Department of Hematology and Medical Oncology, University of Kansas Cancer Center, 2330 Shawnee Mission Parkway, Westwood, KS 66205, USA.

View Book :- https://stm.bookpi.org/HMMR-V10/article/view/1127