Journal of World Future Medicine, Health and Nursing

Artificial intelligence innovations in genetic technology: DNA-based diagnostics for the future of medicine

Thandar Htwe, Aung Myint, Muntasir Muntasir — Tue, 08 Apr 2025 00:00:00 +0700

Advancements in artificial intelligence (AI) are revolutionizing the field of genetic technology, particularly in DNA-based diagnostics, offering promising applications for the future of medicine. The rapid growth of AI in the analysis of genetic data allows for faster, more accurate, and cost-effective diagnostic processes. This study explores the integration of AI innovations in DNA diagnostics and their potential to transform clinical practices. Using a systematic review methodology, this research evaluates the current AI-driven genetic diagnostic technologies, focusing on their impact on disease detection, genetic mutation identification, and personalized treatment strategies. The findings reveal that AI-based tools, such as deep learning and machine learning algorithms, significantly improve the accuracy and speed of genetic diagnoses, particularly in rare genetic disorders and cancers. These technologies are also shown to enhance the predictive power of genetic tests, offering insights into patients' future health risks. The study concludes that AI-driven DNA diagnostics hold the potential to revolutionize medical practice, providing more precise, individualized care while reducing healthcare costs. However, challenges related to data privacy, algorithm transparency, and the need for large-scale clinical validation remain.

Technology-Based Care Model: Building a Sustainable Nursing System in Disadvantaged Areas

Rizka Adela Fatsena, Dina Ahmed, Mona Abdallah, Siska Indrayani — Thu, 10 Apr 2025 00:00:00 +0700

In disadvantaged areas, limited access to healthcare services poses significant challenges to achieving equitable health outcomes. The integration of technology in healthcare systems has been proposed as a solution to bridge gaps in access and quality, particularly in nursing care. This research explores the effectiveness of a technology-based care model in building a sustainable nursing system in underserved regions. The study utilizes a mixed-methods approach, combining quantitative data on health outcomes with qualitative insights from healthcare providers and patients. The findings indicate that technology-based interventions, such as telemedicine, mobile health applications, and remote patient monitoring, led to a 20% improvement in patient outcomes and a 30% reduction in healthcare delivery costs. Additionally, healthcare providers reported increased efficiency and job satisfaction due to the support offered by technology in monitoring patient conditions and facilitating remote consultations. The study concludes that the adoption of technology-driven care models can significantly enhance nursing systems in disadvantaged areas by improving accessibility, efficiency, and sustainability of care. However, challenges related to infrastructure, training, and data security must be addressed to ensure the success of such models. Future research should focus on scaling these models to other resource-limited settings and assessing their long-term impact.

Adaptation to Social Change and Urbanization: Community-Based Health Strategies for Public Health

Sulistyo Andarmoyo, Olivia Davis, Jessica Green — Tue, 08 Apr 2025 00:00:00 +0700

Social change and rapid urbanization have profoundly impacted public health systems, presenting challenges such as rising health disparities, increased prevalence of non-communicable diseases, and the strain on healthcare infrastructure. In response to these challenges, community-based health strategies have gained traction as effective approaches to improving public health outcomes. This research explores the role of community-based health strategies in adapting to the demands of social change and urbanization, with a focus on their impact on health equity, accessibility, and health system resilience. A mixed-methods approach was employed, combining quantitative data from health surveys and qualitative interviews with community leaders and healthcare providers to assess the effectiveness of community-driven health initiatives. The findings indicate that community-based programs significantly improved health outcomes, especially in urban areas facing overcrowding and limited access to healthcare. These programs enhanced health literacy, preventive care, and collaborative efforts between communities and healthcare providers. The study concludes that community-driven health models offer a sustainable solution to public health challenges in rapidly urbanizing regions. The research highlights the importance of integrating these strategies into urban health policy to ensure a more resilient and equitable healthcare system.

The Future of Medical Technology: Recent Innovations in Artificial Intelligence and Robotics for More Precise and Efficient Treatment

Rina Farah, Zain Nizam — Tue, 08 Apr 2025 00:00:00 +0700

The rapid advancement of artificial intelligence (AI) and robotics has transformed the landscape of medical technology, offering unprecedented precision, efficiency, and personalization in patient care. The integration of AI-driven diagnostics and robotic-assisted surgery has improved clinical decision-making, minimized human errors, and enhanced surgical outcomes. This study aims to explore recent innovations in AI and robotics in the medical field, assess their effectiveness in improving treatment precision, and identify challenges in their widespread adoption. A systematic review methodology was employed, analyzing recent peer-reviewed articles, case studies, and reports from medical institutions and technology developers. The findings indicate that AI-powered diagnostic tools significantly enhance early disease detection, while robotic surgery enables minimally invasive procedures with improved accuracy and reduced recovery times. However, challenges such as ethical concerns, high implementation costs, and regulatory hurdles remain key barriers to full-scale adoption. This study concludes that AI and robotics will play an increasingly vital role in modern medicine, revolutionizing healthcare delivery. Further research should focus on optimizing AI algorithms, addressing ethical considerations, and developing cost-effective solutions to ensure broader accessibility and acceptance in medical practice.

Global Prevention of Future Disease Threats: The Role of Technological Solutions in Epidemiology

Khalil Zaman, Jamil Khan — Tue, 08 Apr 2025 00:00:00 +0700

The global landscape of infectious diseases continues to evolve, posing new challenges for public health systems worldwide. With the rise of emerging and re-emerging diseases, it becomes imperative to leverage technological solutions in epidemiology to prevent future health crises. This study investigates the role of advanced technologies such as artificial intelligence (AI), big data analytics, machine learning, and digital health tools in shaping effective disease prevention strategies. The objective is to evaluate the potential of these innovations in forecasting, monitoring, and managing public health threats. Using a systematic review methodology, data were collected from 100 peer-reviewed articles and reports on the application of technological tools in epidemiology. The findings reveal that technological advancements have significantly enhanced the accuracy of disease predictions, real-time monitoring, and rapid response capabilities. Furthermore, AI-driven surveillance systems and big data analytics have proven essential in identifying disease patterns and facilitating early interventions. The study concludes that the integration of technology into epidemiological practices is crucial for proactive global health management. Technological solutions, when effectively implemented, offer scalable and sustainable approaches to preventing future global disease threats.

Utilizing Robotics in Health Care: Increasing the Efficiency and Accuracy of Patient Therapy

Mehdi Karimi, Sahar Yazdani — Tue, 08 Apr 2025 00:00:00 +0700

The healthcare industry has increasingly embraced technological innovations to improve patient care and streamline medical procedures. Among these advancements, robotics has emerged as a powerful tool in enhancing the efficiency and accuracy of patient therapy. Robotics in healthcare can perform tasks such as surgery, rehabilitation, and patient monitoring with precision, leading to better outcomes and reduced human error. This study explores the integration of robotics in healthcare, focusing on its impact on patient therapy, including rehabilitation and therapeutic assistance. Using a mixed-methods approach, this research evaluates both qualitative and quantitative data from healthcare facilities implementing robotic technologies. The findings show that robotic systems have led to a 30% improvement in rehabilitation outcomes, 20% reduction in therapy time, and significant enhancement in treatment accuracy. These results highlight the potential of robotics to not only increase the efficiency of therapy but also provide more personalized and consistent care. The study concludes that the widespread adoption of robotics in healthcare can significantly improve patient therapy and overall healthcare delivery. However, challenges such as cost, integration with existing healthcare systems, and training requirements must be addressed. Future research should focus

Inclusive Approaches in Future Health Policy: Ethical Challenges of Using Artificial Intelligence in Medicine

Hassan Al-Mutawa, Fatima Al-Mazrouei — Tue, 08 Apr 2025 00:00:00 +0700

The rapid integration of artificial intelligence in medicine has sparked significant advancements in patient care, diagnostics, and treatment planning. However, as artificial intelligence technologies become increasingly prevalent in healthcare, they raise complex ethical challenges that must be addressed to ensure their responsible use. These challenges include concerns about data privacy, algorithmic bias, accountability, and the potential for unequal access to artificial intelligence-based medical interventions. This study explores the ethical implications of using artificial intelligence in medicine and proposes inclusive approaches for future health policy. A qualitative research methodology was employed, including expert interviews and policy document analysis, to examine the ethical issues surrounding artificial intelligence integration in medical practice. The findings indicate that while artificial intelligence holds great promise for improving healthcare efficiency and accuracy, its implementation must be accompanied by robust regulatory frameworks that prioritize equity, inclusivity, and accountability. The study emphasizes the need for collaborative policy-making involving stakeholders from various sectors to ensure that artificial intelligence technologies are developed and deployed in ways that benefit all populations, particularly marginalized communities. The research concludes that inclusive approaches to artificial intelligence integration in healthcare policy can help mitigate ethical risks and foster a healthcare system that is both innovative and ethically sound.

Analysis of Risk Factors for Stunting in Toddlers in South Tapanuli Regency in 2024

Evi Irianti, Melva Melva — Sat, 12 Apr 2025 00:00:00 +0700

Stunting is a major public health issue with long-term effects on the quality of human resources. The prevalence of stunting in South Tapanuli Regency increased from 30.8% in 2021 to 39.8% in 2022. This study aims to identify risk factors contributing to stunting in toddlers. The study employs a cross-sectional design with a correlational approach. The sample consists of 350 toddlers selected through purposive sampling, with data collected via structured interviews. The main contributing factors to stunting include a history of low birth weight (p=0.009), the introduction of complementary feeding before six months of age (p=0.000), and incomplete immunization status, which increases the risk of stunting with an odds ratio (OR) of 2.510. Virtual care is associated with a stable or improved HRQOL and patient and family satisfaction in pediatric T1DM. Decision makers need to consider expanding virtual access to pediatric diabetes care that can improve equitable access to quality care across healthcare systems globally.

The Abbasid Era and the Dynamics of Medical Science

Moch. Said, Ajeng Dwi Fatmawati, Muhammad Amiruddin — Tue, 20 May 2025 00:00:00 +0700

The peak of the glory of Islam can be seen from the progress of the Abbasid Dynasty during the leadership of Harun Ar-Rasyid. Because of the rapid progress in all fields, this era was nicknamed as The Golden Age (Golden Age). This progress is seen in various fields ranging from education, economy and infrastructure, making the Abbasid Dynasty highly respected by other nations. Progress is also seen in the field of health and the development of medical science. The Abbasid Dynasty government focused on developing science so that Muslim scientists and Muslim doctors emerged whose knowledge influenced the world of medicine in the world. Starting from Ibn Sina and Ar-Razi who are very famous as the fathers of modern medicine. The purpose of writing this article is to find out the development and progress of the Abbasid Dynasty in the field of medicine and health. The process of making this article uses the (Library Research) method by collecting a number of books, magazines, journals and relevant sources as well as in-depth analysis. Medical science developed rapidly in the Abbasid era where medical figures and techniques emerged that were very influential for the development of medical science and technology today. Ibn Sina became a pioneer in the advancement of health and medical science, he also wrote a book At-Tibb Law which is a reference for medical science throughout the world.