Redefining Medical Education: Balancing Innovation, Expansion and Excellence in the AI Era | Book Publisher International

 

The advent of artificial intelligence (AI) and rapid technological advancements have ushered in a new era in medical education. This monograph, “Redefining Medical Education: Balancing Innovation, Expansion and Excellence in the AI Era,” is a comprehensive academic compilation of 23 chapters that critically examine the evolving paradigms of medical teaching and learning in the 21st century.

 

Bringing together diverse perspectives from specialities such as Paediatrics & Neonatology, General Surgery, Orthopaedics, Radiology, Obstetrics & Gynaecology, and Surgical Superspecialities, the monograph explores how AI and digital tools are transforming medical curricula, clinical training, assessment, research, and faculty development.

 

It highlights key themes such as personalised learning, competency-based education, telemedicine, simulation-based training, ethical use of AI, global collaborations, and equity in medical access and education. The monograph also addresses the pressing need for balancing rapid expansion in medical institutions with sustained quality and academic excellence.

 

Designed for medical educators, postgraduate trainees, policymakers, and healthcare professionals, this work aims to stimulate critical discourse, encourage innovation, and provide strategic insights for shaping the future of medical education in an AI-integrated world—where technological progress harmonises with human values and academic rigour.

 

Author(s) Details

Dr. P. Ramu.
Government Medical College, Srikakulam, Andhra Pradesh, India.

 

Dr. D. Annapurna
Government Medical College, Vizianagaram, Andhra Pradesh, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mono/978-81-991027-5-0

Artificial Intelligence in Radiology and Pathology: Transforming Medical Imaging Interpretation | chapter 5 | Medical Science: Recent Advances and Applications Vol. 4

Artificial intelligence (AI) has revolutionised the fields of radiology and pathology, significantly enhancing the accuracy, efficiency, and accessibility of medical imaging interpretation. AI-driven algorithms, particularly deep learning and machine learning models, have demonstrated remarkable capabilities in detecting, classifying, and segmenting pathological findings in medical images, including X-rays, CT scans, MRIs, and histopathological slides. These advancements not only aid in early disease detection and diagnosis but also facilitate workflow optimisation, reducing radiologists' and pathologists' workload. Furthermore, AI-driven predictive models contribute to precision medicine by enabling personalised treatment plans. However, challenges such as data privacy, ethical concerns, and the need for robust validation limit widespread clinical adoption. This review explores the current applications of AI in radiology and pathology, its impact on diagnostic accuracy, and the challenges that must be addressed for seamless integration into clinical practice.

 

Author (s) Details

Divyesh Goswami

Department of Pathology, Nootan Medical College and Research Center, Visnagar, Gujarat, India.

 

Amar C Sajjan
Department of Microbiology, Chalmeda Anand Rao Institute of Medical Sciences, Karimnagar, Telangana, India.

 

Ruchi Yadav
Department of Pathology, Maharishi Chyawan Government Medical College Koriyawas, Mahendergarh, Narnaul, Haryana, India.

 

Nipa Hathila
Department of Radiodiagnosis, Pacific Medical College and Hospital, Udaipur, Rajasthan, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/msraa/v4/5423

Epidemiological Information on Anatomical Variations of the Sternum: Sternal Foramen and Variant Xiphoid Morphology in Dried Adult Human Sternum in Ethiopia | Chapter 1 | Achievements and Challenges of Medicine and Medical Science Vol. 6

Background: The human sternum comprises three components such as the manubrium, the mesosternum (body), and the xiphoid process. The sternum exhibits unique anatomical variations with major clinical and forensic implications. Purpose: This study is devoted to providing baseline epidemiological information about the sternal foramen and variant xiphoid morphology in Ethiopia. Two extremely interesting and unusual variations of the sternal foramen are also discussed.

Methods: This observational study was carried out using dried adult human sternum obtained from skeletal remains samples brought for medicolegal examination over a period of 4 years. A total of 94 dried adult human sternums (66 males (70.2%) and 28 females (29.8%)) were obtained with an age range of 21 to 57 years and a mean age at death of 38.383 ± 11.3480 years. Data were analyzed using SPSS version 26.0. Continuous data were described in terms of the mean and compared using the Mann–Whitney U test. Dried human sternum specimens were morphologically examined, and morphometric parameters were recorded and photographed.

Results: A sternal foramen was found in 18 specimens (19.1%); 17 were male and one was female. A single sternal foramen was observed in 83.3% (n=15/18) of the sternal bodies and 11.1% (n=2/18) of the xiphoid processes (both males). In addition, a double sternal foramen was observed in a single male specimen on the mesosternum and xiphoid process. The most common sternal foramen site was at the fifth costochondral junction level. The xiphoid process was present in 77 samples and ended as a single process in 83.1% (n=64/77) of samples. In 15.6% (n=12/77) of the samples, the xiphoid process was bifurcated and trifurcated in a single male (1.3%) specimen. The incidence of Sternal foramen varies in different studies from different populations and reported incidence data on Sternal foramen from different populations ranging from 3.1 to 18.3%.

Conclusions: The sternal foramen and variation in xiphoid morphology are common anatomical variations in Ethiopia. The findings of the current study highlight the necessity of strict precautionary measures during sternal procedures in this study population. Clinicians, radiologists, and anthropologists need to be aware of these variations, and their presence should be taken into consideration in everyday practice. In addition, such incidental findings during radiologic and autopsy procedures should be properly evaluated to avoid misdiagnosis and misinterpretation of such findings as traumatic or pathologic conditions.

 

Author (s) Details

Alemayehu Shiferaw Lema
Department of Forensic Medicine and Toxicology, St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia.

Amanuel Oljira Raga
Department of Forensic Medicine and Toxicology, St. Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia.

 

Please see the book here:- https://doi.org/10.9734/bpi/acmms/v6/1321

Impact of Artificial Intelligence in the Field of Health Care | Chapter 1 | Contemporary Perspective on Science, Technology and Research Vol. 5

 AI undoubtedly plays an exponential role in healthcare and medicine. Several researches revealed that digitization may help health care professionals in making decisions and discoveries much faster than before. Looking at the advances in AI, medical practice in the forthcoming years might be like where a patient would have to see the computer for initial diagnosis before visiting a doctor. This chapter discusses the algorithm of artificial intelligence, and the impact of artificial intelligence in the health care system. such as virtual medical assistant, automated image diagnosis, personal health companions, oncology, cardiology, radiology, AI powered chatbots. AI may replace humans for initial diagnosis both in developed and developing countries shortly. AI and ML is making people rely on them for basic work flows, decision making and makes people trust them for safety and accuracy.

Author(s) Details:

Ragavi V.,
Department of Science and Humanities, Sri Krishna College of Engineering and Technology, Coimbatore, 641008, India.

SanthaSheela A. C.,
Department of Computer Science, Sathyabama Institute of Science and Technology, Chennai, India.

Geetha Narayanan Kannaiyan,
Department of Science and Humanities, Sri Krishna College of Engineering and Technology, Coimbatore, 641008, India.

Please see the link here: https://stm.bookpi.org/CPSTR-V5/article/view/13272

Pyogenic Granuloma of Nasopharynx: A Rare Case Report | Chapter 9 | Highlights on Medicine and Medical Science Vol. 13

 This article describes the surgical treatment of a 47-year-old female patient with pyogenic granuloma. To our knowledge, there has never been a report of a PG emerging from the nasopharynx. The cause of pyogenic granuloma (PG) is unknown; it is a reactive tumor-like lesion that develops in response to a variety of stimuli. On October 15th, 2018, a 47-year-old Saudi woman appeared with a month's worth of nasal blockage. On/off epistaxis, headache, and allergy symptoms were all part of the patient's complaint. She had a pedunculated nasopharyngeal lesion on examination. A tumour in the right nasal cavity was discovered by radiological examinations. a nasopharyngeal lesion that does not spread to surrounding areas The lesion was removed with a nasoscope and the base was cauterised. Vascularized granulation tissue with ulcerated epithelium and fibrinous exudates was discovered on histopathology. Nasopharyngeal pyogenic granuloma is a rather uncommon condition. It's one of the possible causes of nasal haemorrhage.

Author (S) Details

Kholood S. Assiri
Department of ORL-HNS, Khamis Mushayt General Hospital, Khamis Mushayt, Kingdom of Saudi Arabia.

Mohammad S. Al-Ahmari
Department of ORL-HNS, Khamis Mushayt General Hospital, Khamis Mushayt, Kingdom of Saudi Arabia.

View Book :- https://stm.bookpi.org/HMMS-V13/article/view/2728

Study on Simulators of Pancreatic Adenocarcinoma: An Approach to Avoid Misdiagnosis | Chapter 6 | Highlights on Medicine and Medical Science Vol. 8

 Examinable neoplastic, inflammatory, and benign pancreatic as well as non-pancreatic processes that can mimic pancreatic adenocarcinoma will be shown. Pancreatic adenocarcinoma (PA) is one of the most aggressive cancers, accounting for the fourth highest number of cancer-related fatalities in the Western world. When compared to normal pancreatic tissue modelling PA, focal fatty infiltration is usually most evident in the head of the pancreas, and contrast enhancement on CT usually shows as a region with reduced contrast matherial amplification. In most cases, imaging of a hypoathenuating lesion in the head of the pancreas indicates cancer. However, radiologists must exercise caution because a false positive diagnosis can result in unneeded surgery, which can be dangerous.

Author (s) Details

Atanas Dimitrov Hilendarov
Department of Diagnostic Imaging, Faculti of Medicine, Medical University, Plovdiv, Bulgaria.

Alexandar Asenov Georgiev
Department of Diagnostic Imaging, Faculti of Medicine, Medical University, Plovdiv, Bulgaria.

Lyubomir Georgiev Chervenkov
Department of Diagnostic Imaging, Faculti of Medicine, Medical University, Plovdiv, Bulgaria.

View Book :- https://stm.bookpi.org/HMMS-V8/article/view/2166