Claim Missing Document
Check
Articles

Found 5 Documents
Search

The Future of Medicine: Harnessing the Power of AI for Revolutionizing Healthcare Alexandra Harry
International Journal of Multidisciplinary Sciences and Arts Vol. 2 No. 1 (2023): International Journal of Multidisciplinary Sciences and Arts, Article June 2023
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v2i1.2395

Abstract

Artificial intelligence (AI) has the potential to completely change how healthcare is delivered, revolutionizing the healthcare sector. Precision diagnosis, proactive disease prevention, personalised treatment plans, real-time monitoring and intervention, improved medical imaging, streamlined healthcare workflows, ethical considerations, and the potential future implications of AI in healthcare are all explored in this paper. The first section describes how precision diagnosis using AI technologies is improving diagnostic accuracy. Personalised treatment regimens and earlier disease detection are made possible by machine learning algorithms' analysis of enormous volumes of patient data. Additionally, AI makes it possible to actively prevent disease by using predictive analytics to identify those who are most likely to develop a particular condition, enabling early intervention and tailored preventive actions. The second segment focuses on how AI is transforming therapeutic approaches. AI algorithms create individualised treatment regimens by analyzing patient data, including genetics, biomarkers, and information on therapy response. This maximizes treatment efficacy and minimizes side effects. Additionally, wearable technology and remote monitoring devices powered by AI allow for real-time monitoring and intervention, improving patient safety and lowering hospital readmissions. Examines how AI has affected medical imaging. Radiologists' efficiency and accuracy in identifying anomalies are increased by deep learning algorithms' analysis of complicated medical pictures like CT scans and MRIs. As a result, diagnoses are made more quickly and accurately, allowing for quicker interventions and better patient outcomes. The fourth chapter examines how AI streamlines medical procedures. Administrative responsibilities are reduced and errors are minimized by automating operations like appointment scheduling and documentation. By offering timely support and triaging symptoms, intelligent catboats and virtual assistants increase patient involvement and happiness. The fifth segment talks with ethical issues related to AI in healthcare. In order to create and use AI algorithms responsibly, patient privacy, data security, and bias mitigation are essential. Fair and equitable healthcare practices must be ensured by ethical standards and legal requirements. The abstract wraps off with a preview of the potential effects of AI on healthcare delivery in the future. Emerging medical technologies including telemedicine, robotics, predictive analytics, and AI-assisted surgery show immense promise for revolutionizing the industry. To overcome obstacles, maximize advantages, and guarantee a human-centric approach in the integration of AI in healthcare, cooperation between healthcare practitioners, technologists, policymakers, and ethicists is essential.
AI's Healing Touch: Examining Machine Learning's Transformative Effects on Healthcare Alexandra Harry
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 4 (2023): BULLET : Jurnal Multidisiplin Ilmu (INPRESS)
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

In the field of healthcare, artificial intelligence (AI) has emerged as a paradigm-shifting force, upending established procedures and promising unmatched improvements. This in-depth analysis examines the varied ways in which AI is being used in healthcare, focusing on its transformational potential, the difficulties it presents, and the crucial ethical issues that must be taken into account when it is used. Through a number of topic categories, the article opens by highlighting the vast range of AI's impact on healthcare. Each section delves into a specific aspect of AI's influence, illuminating subjects including clinical decision-making, customized medicine, diagnostic accuracy, and drug discovery. The complex interaction between AI and medical imaging is revealed, as well as the possibility for AI systems to examine enormous datasets. The promise of AI in changing clinical decision-making is further examined in the article, with a focus on its role in patient management and its capacity to overcome ethical dilemmas. The ethical environment that surrounds AI-driven healthcare is a major area of focus. The study highlights the value of protecting patient data privacy and the necessity of secure data transmission and compliance with data protection laws. It also addresses the widespread worry about bias in AI algorithms, highlighting the necessity of objective training data and rigorous bias detection procedures. When openness and accountability are pitted against the complexity of complicated algorithms, the interpretability of AI-generated insights becomes a problem. The assessment looks more closely at the moral issues surrounding patient autonomy and the changing responsibilities of healthcare providers. It advocates for open communication between AI, patients, and healthcare practitioners as it navigates the complex balance between innovation and patient welfare. The article also emphasizes the need for strong ethical frameworks and rules to appropriately govern AI implementation in healthcare. The thorough investigation ends with an analysis of the potential applications of AI in healthcare. It describes the possibility for improved medical operations, drug discovery, remote patient monitoring, and diagnostic improvement. In order to leverage AI's transformative potential while protecting patient interests, healthcare practitioners, data scientists, policymakers, and ethicists must work together. This is highlighted in the abstract. The review captures the remarkable change AI has brought about in healthcare. The study emphasizes the critical need of simultaneously exploiting AI's promise and attending to the ethical and regulatory issues that arise as technology develops and AI becomes more integrated. In the end, the abstract presents a comprehensive picture of AI's changing healthcare role and its potential to transform patient care, medical procedures, and the entire structure of the healthcare sector.
Navigating the Complex Intersection of Diplomacy, Business, and Politics Alexandra Harry
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 5 (2023): BULLET : Jurnal Multidisiplin Ilmu
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The confluence of diplomacy, business, politics, and the social sciences has emerged as a distinctive aspect of international relations in our dynamic global environment. In-depth analysis of the complex interactions between various fields is provided in this work, along with a look at how they have a wide range of effects. We start by looking at how diplomacy has changed over time, showing how it has gone from being a state-centric activity to one that increasingly include non-state entities like multinational corporations and NGOs. A recurring concept that emphasizes the significance of diplomatic tactics in the success of global company is business diplomacy. It is explained how politics affect international business practices and how governments shape the laws, rules, and geopolitical environments that affect enterprises all over the world. This dynamic takes political lobbying, moral quandaries, and sustainable behaviors into consideration. The report also emphasizes the crucial importance of social sciences in diplomatic discussions, highlighting how insights from economics, sociology, anthropology, and psychology understanding society dynamics and human behavior improve diplomatic efficiency. The study examines the function of political diplomacy in corporate partnerships and considers how diplomatic efforts might encourage, shape, and support global partnerships and joint ventures. This topic is fundamentally influenced by geopolitical threats, transparency issues, and ethical problems. Diplomacy-business relations have socioeconomic effects that are brought to light, emphasizing their benefits for economic growth, job creation, and labor mobility while also addressing issues with income inequality, environmental sustainability, and public health. This link does present some ethical problems, though. Conflicts of interest, challenges with transparency and accountability, lobbying ethics, and the precarious balance between business interests and social and environmental duties are among topics covered in the paper. In this interconnected world, it is crucial to take ethical issues such data privacy and security, corruption risks, cultural sensitivity, and human rights into account. The article emphasizes the value of moral leadership, moral standards, and responsible conduct in business and diplomacy. This study provides a comprehensive understanding of the intricate interactions between diplomacy, commerce, politics, and the social sciences, demonstrating their multifaceted relationships and emphasizing the moral dilemmas and obligations that occur in this intersection. Real-life case studies and examples help to highlight the difficulties and offer suggestions for promoting ethical and moral behavior in our linked world.
Revolutionizing Healthcare: How Machine Learning is Transforming Patient Diagnoses - A Comprehensive Review of AI's Impact on Medical Diagnosis Alexandra Harry
BULLET : Jurnal Multidisiplin Ilmu Vol. 2 No. 4 (2023): BULLET : Jurnal Multidisiplin Ilmu (INPRESS)
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

A major transformation in patient diagnoses, individualized therapies, and healthcare delivery has been sparked by the intersection of machine learning and healthcare. This essay explores the complex interactions between innovative technology and compassionate care, shedding light on how the blending of AI-driven insights and human expertise is altering the healthcare industry. The trip starts with a breakdown of the fundamental ideas behind machine learning in healthcare. We investigate how machine learning algorithms can find hidden patterns in complex medical data, allowing for risk stratification and early disease identification. The application of machine learning to medical imaging, particularly radiology, stands out as a key development that improves diagnostic precision and speeds up treatment choices. Diagnostic aids are becoming an increasingly important part of healthcare professionals' toolkits as the applications of machine learning grow. These tools enhance clinical decision-making by analyzing patient data to produce potential diagnoses and provide treatment suggestions, adding a new level of interaction between human intuition and AI-driven insights. The paper explores the problems with conventional patient diagnosis, such as human error, diagnostic accuracy variability, and obstacles in diagnosing unusual diseases. An answer appears in the form of machine learning, which has the ability to lower errors, standardize diagnoses, and improve the precision of identifying rare diseases. When integrating machine learning in healthcare, ethical and legal issues take center stage. The critical pillars that direct the appropriate use of AI-driven insights are patient autonomy, data privacy, algorithmic bias, and interpretability. In order to ensure patient trust, data security, and moral behavior, it is crucial to navigate these issues. The article provides compelling case studies that demonstrate machine learning's revolutionary effects on the healthcare industry. These case studies highlight concrete accomplishments that improve patient outcomes, redefine diagnostic accuracy, and shape a healthcare landscape that is increasingly precise and patient-centric. They range from radiology and early disease detection to predicting infectious disease outbreaks and enabling personalized treatments. The combination of machine learning and healthcare is an example of how data-driven innovation has the ability to completely transform a sector with a strong foundation in human compassion. The research emphasizes the mutually beneficial interaction between machine learning and human expertise while highlighting the necessity of striking a balance between the revolutionary potential of technology and ethical considerations and patient-centered treatment. The revolutionary potential of machine learning in healthcare shines as a ray of hope for a future where progress melds with tradition to reimagine the art and science of healing as we proceed on our path.
Revolutionizing Healthcare: The Role of Artificial Intelligence in Antibiotic Stewardship and Resistance Management Alexandra Harry
International Journal of Multidisciplinary Sciences and Arts Vol. 3 No. 2 (2024): International Journal of Multidisciplinary Sciences and Arts, Article April 202
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/ijmdsa.v3i1.3943

Abstract

Artificial intelligence (AI) has great potential to transform the way antibiotics are managed in healthcare by providing creative ways to fight antibiotic resistance and enhance patient outcomes. This paper examines the various aspects of AI's function in the management of antibiotics, including diagnosis, tailored treatment, infection surveillance, and future implications. The talk focuses on the potential advantages of AI-driven methods, such as improved diagnostic precision, customized treatment plans, and proactive monitoring of patterns of antibiotic resistance. But there are several obstacles to overcome before AI can be fully applied in the healthcare industry. These include issues with technical complexity, data accessibility and quality, clinical acceptability, regulatory concerns, and long-term financial viability. Collaboration amongst partners, financial support for infrastructure and resources, and a dedication to moral, patient-centered care are all necessary to meet these obstacles. Notwithstanding these challenges, AI-driven antibiotic management has enormous potential to revolutionize global patient outcomes, fight antibiotic resistance, and change healthcare delivery.