Volume-5 Issue-4, May 2025 – International Journal of Preventive Medicine and Health (IJPMH)

D107705040525

IJPMH Journal — Sat, 03 May 2025 05:58:13 +0000

The International Journal of Preventive Medicine and Health (IJPMH) has ISSN 2582-7588 (online), open-access, peer-reviewed, periodical bi-monthly international journal, which is published by Lattice Science Publication (LSP) in March, May, July, September, November and January. The journal aims to publish high-quality peer–reviewed original articles in the area of Preventive Medicine and Health that covers such as the Nipah Virus, COVID-19(Corona Virus), Henipa Viruses, Antibiotic Resistance, Breastfeeding, Behavioural Health, Clinical Trials, Community Engagement, Community Health, Child/Adolescent Health, Chronic Diseases, Disease Transmission, Health Informatics, Health Care Management, Health Care Quality, Efficiency, Human Nutrition, Immunization, Maternal & Child Health, Primary Healthcare, Public Health, Reproductive Health, Vaccination, Clinical and Epidemiological Diagnosis and Management, Health care, Epidemiology, Biostatistics, Public Health Administration, Health Care Delivery, National Health Problems, Medical Anthropology, Social Medicine. #Nipah Virus #COVID-19(Corona Virus) #Henipa Viruses #Antibiotic Resistance #Breastfeeding #Behavioural Health #Clinical Trials #Community Engagement #Community Health #Child/Adolescent Health #Chronic Diseases #Disease Transmission #Health Informatics #Health Care Management #Health Care Quality, Efficiency #Human Nutrition #Immunization #Maternal & Child Health #Primary Healthcare #Public Health #Reproductive Health #Vaccination #Clinical and Epidemiological Diagnosis and Management #Health Care #Epidemiology #Biostatistics #Public Health Administration #Health Care Delivery #National Health Problems #Medical Anthropology #Social Medicine #PhD #Academic #Scopus #SCI #LatticeScience #Springer, #ScienceDirect #IEEE #Mendeley #Research #Scholarship #UGC #SSRN #LatticeScience #ESCI #Science #Journal #Conference #SSRN #PubLons

Promoting Good Health and Well-being: Essential in Leading to Up-gradation of Living Conditions
Radhika Kapur

Dr. Radhika Kapur, Pedagogy and Organizational Culture in Nursery Schools, Delhi University, New Delhi, India.

Abstract: The main objective of this research paper is to generate information regarding the meaning and significance of promoting good health and well-being. Individuals from all age groups, occupations, communities, and socio-economic backgrounds need to access information regarding various factors that promote good health and well-being, both physically and psychologically. All types of factors must be put into operation in a well-organised and regimented manner. In other words, positivity needs to be reinforced in all the factors. It is understood that improving overall living conditions is regarded as one of the primary goals for individuals from all communities and socio-economic backgrounds. To achieve this goal, one must consider several factors, i.e. education, careers, employment opportunities, resources, assets, property, health, well-being, family, relationships, personality traits and overall living conditions. All factors must be implemented adequately so that one can maintain physical and psychological health. Hence, to carry out all tasks and activities successfully, one may not be immune to health problems and illnesses, but one needs to be psychologically sound. Therefore, it is widely understood that promoting good health and well-being is crucial to enhancing living conditions. The primary concepts examined in this research paper are the understanding of the meaning and significance of promoting good health and well-being, the measures to be implemented for achieving this goal, and the benefits of promoting good health and well-being.

Keywords: Effective, Enhancement, Health, Personality Traits, Physical, Psychological, Standards of Living, Well-being.
Scope of the Article: Community Health

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D107105040525

IJPMH Journal — Sat, 03 May 2025 05:51:32 +0000

Enhancing Virtual Assistance for Mental Health Support
Ankit Baghel¹, Akansha Pawar², Janvi Hatwar³, Devansh Shrivastav⁴, Shruti Thakur⁵

¹Ankit Baghel, UG Student, G H Raisoni College of Engineering, Nagpur (Maharashtra), India.

²Akansha Pawar, UG Student, G H Raisoni College of Engineering, Nagpur (Maharashtra), India

³Janvi Hatwar, UG Student, G H Raisoni College of Engineering, Nagpur (Maharashtra), India

⁴Devansh Shrivastav, UG Student, G H Raisoni College of Engineering, Nagpur (Maharashtra), India

⁵Dr. Shruti Thakur, Assistant Professor, G H Raisoni College of Engineering, Nagpur (Maharashtra), India

Abstract: This research introduces Enhancing Mental Health Support through Virtual Assistance by an efficient and Comprehensive Approach. Virtual assistant features empathetic conversation capabilities, regular symptom tracking, suggestions, and connections with psychiatrists. The project’s objectives include assessing the efficacy of virtual assistance in enhancing user engagement and mental health outcomes, as well as exploring users’ perceptions of privacy and the effectiveness of this approach. We investigate the efficacy of virtual assistants in crisis intervention, ongoing therapy support, and providing coping strategies, emphasising their role in accessibility and anonymity. Furthermore, the research explores ethical considerations, including data privacy, the importance of human oversight, and the potential for virtual assistants to complement traditional therapeutic practices. The increasing demand for mental health support has led to the exploration of innovative solutions, with virtual assistance emerging as a promising avenue. This paper examines the enhancement of virtual assistants in providing mental health support by integrating advanced technologies, including natural language processing (NLP) and machine learning (ML). These systems can offer personalized responses and resources tailored to individual needs by analysing user interactions and emotional cues.

Keywords: Virtual Assistance, Efficient Conversation, Connection with A Psychiatrist, and Regular Symptom Tracking.
Scope of the Article: Maternal Health

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D106605040525

IJPMH Journal — Sat, 03 May 2025 05:42:11 +0000

Applications of Microfluidics in Biomedical and Pharmaceutical Fields -An Overview
Stefna Varghese¹, Poonam Parashar², Pragya³

¹Stefna Varghese, Student, Department of Pharmacy, Amity Institute of Pharmacy, Amity University, Lucknow (Uttar Pradesh), India.

²Dr. Poonam Parashar, Associate Professor, Department of Pharmaceutics, Amity Institute of Pharmacy, Amity University, Lucknow (Uttar Pradesh), India.

³Dr. Pragya, Assistant Professor, Department of Pharmaceutics, Amity Institute of Pharmacy, Amity University, Lucknow (Uttar Pradesh), India.

Abstract: The precise manipulation of fluids at the microscale level within minuscule channels measuring tens to hundreds of micrometres is the subject of the multifaceted field of microfluidics. This technology has transformed the pharmaceutical industry by enabling miniaturised, highthroughput, and economical drug discovery, formulation, and delivery solutions. Creating sophisticated drug delivery systems, such as nanoparticles and liposomes, has become significantly simpler due to this method’s ability to precisely control fluid dynamics, which enables faster reaction kinetics and improved drug encapsulation. Beyond drug formulation, microfluidic platforms enable disease modelling, toxicity assessment, and pharmacokinetic/pharmacodynamic analysis, providing a quick and efficient alternative to conventional techniques. Additionally, devices like microfluidic chips integrate multiple analysis processes into a single device, leading to reduced reagent consumption and enhanced research opportunities. Furthermore, microfluidics is vital in personalised medicine and point-of-care diagnostics, offering rapid, more accurate testing for a customised treatment strategy. The increased use of microfluidics in pharmaceutical research is promising for facilitating faster drug discovery, enhancing individualised medicine, and improving point-of-care diagnostic testing. This paper discusses the definition, importance, and applications of microfluidics in the pharmaceutical field, with a focus on its implications for the future of drug discovery and healthcare.

Keywords: Microfluidics, Drug Discovery, Pharmaceutical Research, Point-of-Care Diagnostics, Personalized Medicine.
Scope of the Article: Health Care Management

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C106405030325

IJPMH Journal — Sat, 03 May 2025 05:35:02 +0000

Diagnosis of Retinal Detachment via Blood Vessel Analysis using Multi threshold Image Binarization
Anjali Arun Rokde¹, Dnyaneshwari Patil², Sharayu Rajesh Patil³

¹Anjali Arun Rokde, Assistant Professor, MGMU Dr. G.Y. Pathrikar College of CS & IT, Chh. Sambhajinagar, Aurangabad (Maharashtra), India.

²Dr. Dnyaneshwari Patil, Assistant Professor, MGMU Dr. G.Y. Pathrikar College of CS & IT, Chh. Sambhajinagar, Aurangabad (Maharashtra), India.

³Sharayu Rajesh Patil, Regulatory Affairs Specialist, Northeastern University, Boston Massachusetts, Aurangabad (Maharashtra), India.

Abstract: In the eye retina is the innermost layer. The retina is the light-sensitive tissue lining the back of the eye. Retinal detachment is a disorder of the eye. It is described as a critical condition in which all retinal layers are pulled away from their normal position. Retinal detachment can lead to visual impairment or loss of vision. Therefore, diagnosing retinal detachment disease at an earlier stage is crucial. This study aims to analyse the position of retinal detachment about the retina’s blood vessels. The process of extracting the normal and detached retinal positions is conducted in four steps: image pre-processing, applying a Filter, multi-thresholding with image binarisation, extracting the retinal blood vessels, and extracting the position of Retinal detachment disease. In this research, we utilised the local dataset of Aravid Eye Care Hospital from the IEEE website, which contains retinal detachment fundus images. In this work, we extract one feature of Retinal Detachment disease, i.e., the Retina’s blood vessels. Additionally, we compare the healthy retina with the detached retina in its position relative to the blood vessels.

Keywords: Retinal Detachment, Feature Extraction, Blood Vessels, Database, Preprocessing.
Scope of the Article: Community Health

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A454514011024

IJPMH Journal — Sat, 03 May 2025 05:22:58 +0000

An in-Depth Review of Cardiovascular Disease Prognosis Using Algorithms Based Upon Artificial Intelligence
Divyasri. S. R¹, A. Rama Prasath²

¹Divyasri. S. R, Department of Computer Application, Hindustan Institute of Technology and Science, Kelambakkam (Tamil Nadu), India.

²A. Rama Prasath, Department of Computer Application, Hindustan Institute of Technology and Science, Kelambakkam (Tamil Nadu), India.

Abstract: High mortality rates are a result of cardiovascular diseases (CVDs), which pose serious global health challenges. It is possible to decrease the risk of having an acute myocardial infarction and the mortality rate among people with cardiovascular diseases by promptly detecting cardiovascular events. The multifaceted pathological techniques and diverse determinants engaged in the menace assessment of CVDs, heart attacks, interpretations of medical imaging, therapeutic decisionmaking, and diagnosis of disease necessitate revisions to conventional data analysis methods. Artificial intelligence (AI) is a term used to describe technology that uses complex computer algorithms to analyse massive amounts of data. AI is now widely used in the medical field. AI methods have proven to be able to diagnose and treat a variety of CVDs more quickly, including hypertrophic cardiomyopathy, congenital heart disease, valvular heart disease, atrial fibrillation, and heart failure. We examined 92 papers from reliable sources, including Google Scholar, Springer, Elsevier, and other reputable databases, for this comprehensive review. AI has shown great promise in clinical settings for the diagnosis of cardiovascular diseases, the improvement of supporting tools, the classification and stratification of disorders, and the prediction of outcomes. Intellectual AI systems have been carefully designed to analyse complex relationships in large datasets of healthcare data, enabling them to perform more complicated tasks than traditional methods.

Keywords: Cardiovascular disease, Artificial Intelligence, Deep learning, Machine Learning, Heart disease, Feature selection, Pre-processing.
Scope of the Article: Community Health

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Volume-5 Issue-4, May 2025 – International Journal of Preventive Medicine and Health (IJPMH)

D107705040525

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D107105040525

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D106605040525

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C106405030325

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A454514011024

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