The potential of AI technologies to revolutionize clinical practice in the field of urology is investigated, with a specific focus on the Moroccan healthcare system, and the ethical considerations and practical challenges involved in integrating AI into medical environments are addressed.
Artificial intelligence (AI) has the potential to transform the healthcare industry by improving the quality and efficiency of healthcare services. AI in healthcare can revolutionise various elements of patient care and administrative processes. The primary goal of this investigation was to investigate the uses of AI for the detection, identification and diagnosis of various diseases and health disorders and provide future implications to professionals in the medical and medical informatics fields in AI abilities and competencies. A survey was administered to many doctors working in various healthcare settings across India, and the responses were collected and analysed using statistical methods. According to the report, most healthcare professionals thought AI significantly impacted healthcare quality and effectiveness, with the potential to lower costs and boost patient outcomes. The findings of this study will enhance the ongoing discussions on the incorporation of AI in healthcare and offer suggestions for long-term progress in healthcare. The results of this study add to the expanding body of knowledge about how AI is affecting healthcare and shed light on the viewpoints of healthcare workers, which can help policymakers and decision-makers in the healthcare sector make decisions that will promote sustainable development.
Ikshita Rao, J. Shivarama, A. Sahu· Journal of Health Management· 0 citations
Relevance
. The modern healthcare system is entering a stage of deep digital transformation, with artificial intelligence becoming a key tool. The development of algorithms, the growth of computing power and the accumulation of large amounts of medical information have made it possible to move from theoretical models to real digital solutions in clinical and management practice. From a managerial point of view, artificial intelligence opens up new opportunities for analyzing big data, predicting the needs of the population for medical care, optimizing patient routing and resource allocation. The use of intelligent analytical platforms helps to increase the efficiency of medical organizations, reduce the administrative burden and implement the principles of quality management. From a clinical perspective, artificial intelligence is becoming a tool for improving the accuracy of diagnosis, early detection of diseases, personalization of treatment and evaluation of the effectiveness of therapy. Machine learning algorithms are actively used in radiology, cardiology, oncology and telemedicine, providing an additional level of expert support to the doctor and reducing the likelihood of diagnostic errors. Special attention is paid to issues of ethics, clinical verification of results, protection of personal data and preservation of the leading role of the doctor as a responsible decision-making subject. The article examines the organizational, professional and socio-cultural aspects of the use of artificial intelligence in healthcare in the Republic of Uzbekistan.
The purpose of the study
: to summarize modern approaches to the use of artificial intelligence in healthcare, evaluate the clinical and managerial possibilities of its use, identify limitations and ethical aspects.
Materials and methods
. An analytical review of international publications (WHO, NEJM, JAMA, Nature Medicine, and others), as well as regulatory documents on digital healthcare, was conducted. A descriptive and analytical method was used to summarize data on clinical and managerial applications of artificial intelligence.
Results
. The use of artificial intelligence is highly effective in the following areas: medical image analysis (computer and magnetic resonance imaging, X-ray); disease prediction (cardiovascular, oncological, endocrine); clinical decision support; monitoring of chronic patients; patient flow management; optimization of healthcare resources. In a management context, artificial intelligence makes it possible to analyze large amounts of data, predict the burden on the healthcare system, and increase the efficiency of resource allocation. Despite its high productivity, its implementation is accompanied by a number of limitations. The main problems are the quality of the source data, the risk of algorithmic errors, and limited interpretability of the models. Ethical issues are of particular importance: the protection of personal data, the transparency of algorithms and the preservation of the role of the doctor as a subject of decision-making. Artificial intelligence does not replace clinical thinking, but acts as a tool to enhance it. Thus, a new healthcare model based on the use of digital technologies is being formed.
Conclusion
. Artificial intelligence is an important tool for healthcare transformation, improving the quality of medical care and management efficiency. Its application requires the development of digital infrastructure, the training of medical personnel and the formation of a new ethical and legal model.
Artificial intelligence (AI) is widely regarded as one of the most promising innovations in healthcare, yet its adoption in routine clinical practice remains limited. Only a small proportion of AI applications developed in research settings are successfully integrated into healthcare delivery. Major barriers include poor interoperability with existing health information systems, complex regulatory requirements, limited scientific evidence, and the lack of clear clinical guidelines. Many AI tools have been evaluated through methodologically weak studies, often retrospective and lacking external validation, contributing to skepticism among healthcare professionals. Additional challenges involve healthcare professionals' education and training, algorithm transparency, and the ability of healthcare organizations to effectively incorporate these technologies into clinical workflows. To promote the safe and effective adoption of AI, stronger clinical evidence, structured training programs, and organizational models capable of supporting its implementation are required. Addressing these issues is essential to ensure that AI can deliver meaningful benefits for patients, healthcare professionals, and healthcare systems.
Eugenio Santoro· Recenti progressi in medicin...· 0 citations
To improve integration, stakeholders should begin any new POCUS AI development project by first examining the different domains where POCUS AI applications are most needed, including education, clinical practice, workflow, research, and administration.
Robinson M. Ferre, Rachel B. Liu, HF Samuel Lam et al.· Journal of the American Coll...· 0 citations
A narrative review synthesises the current literature, regulatory frameworks, and ethical guidelines about the medicolegal dimensions of AI in healthcare, without adherence to a formal systematic review protocol, to address significant medico-legal and ethical challenges facing AI in healthcare.
M. Niriella, Krishanni Prabagar, I. Wijesingha et al.· AI and Ethics· 0 citations
In the healthcare industry, artificial intelligence (AI) has significantly enhanced treatment plans, pharmaceutical advancements, hospital administration, and diagnostic precision. This review examines the integration of AI across domains, including robotic surgery, drug development, medical imaging, epidemiology, and clinical decision-making. Techniques like deep learning and natural language processing (NLP) have proven remarkably effective in the domains of medical image interpretation, illness trajectory prediction, and healthcare infrastructure optimisation. However, increasing the fairness and transparency of AI is crucial to gaining the trust of patients and medical professionals. Looking forward, future advancements in medical AI are anticipated to be primarily driven by generative AI, federated learning, and multimodal AI. Instead of taking the place of human knowledge, artificial intelligence (AI) will be used as a supplementary tool to help healthcare professionals make better clinical decisions by giving them data-driven insights. It will be crucial to guarantee sustainable AI deployment and foster global cooperation to make AI-driven medical solutions inclusive and accessible. The success of AI in imaging will be measured by worth creation, which includes better patient outcomes, faster turnaround, higher diagnostic certainty, and a higher quality of work life for radiologists. AI offers a novel and fascinating collection of methods for analysing image data. Radiologists will likely be at the forefront of AI's medical applications as they explore these new possibilities.
Saba Waleed, Syed Zulfiqar Ali Shah, Rubia Anjum Tariq et al.· Veredas do Direito· 2 citations
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