Lab on a Chip, Journal Year: 2024, Volume and Issue: 24(7), P. 1833 - 1866
Published: Jan. 1, 2024
Wearable devices are increasingly popular in health monitoring, diagnosis, and drug delivery. Advances allow real-time analysis of biofluids like sweat, tears, saliva, wound fluid, urine.
Language: Английский
International Medical Science Research Journal, Journal Year: 2024, Volume and Issue: 4(2), P. 126 - 140
Published: Feb. 2, 2024
The fusion of Artificial Intelligence (AI) and healthcare heralds a new era innovation transformation, yet it is not without its ethical quandaries. This comprehensive review traverses the intricate landscape where AI meets healthcare, delving into dilemmas that arise alongside practical applications. considerations span spectrum, encompassing issues patient privacy, transparency, accountability, inadvertent perpetuation biases within algorithms. Privacy concerns emerge as central dilemma providers leverage to process vast amounts data. Striking delicate balance between harnessing power for diagnostic predictive purposes safeguarding sensitive medical information critical challenge. Moreover, scrutinizes implications algorithms their potential perpetuate biases, inadvertently exacerbating health disparities. A nuanced examination bias mitigation strategies becomes imperative ensure technologies contribute equitable outcomes. In tandem with considerations, illuminates applications reshaping landscape. AI-driven diagnostics, modeling, personalized treatment plans transformative tools, enhancing clinical decision-making efficient allocation resources, streamlined workflows, acceleration drug discovery processes showcase tangible benefits integration. aspires guide practitioners, policymakers, technologists in navigating crossroads healthcare. By fostering an awareness pitfalls emphasizing responsible development, stakeholders can collaboratively shape future augments delivery, upholds standards, ultimately improves quality care. Keywords: AI, Healthcare, Ethics, Review, Application.
Language: Английский
Citations
26
Journal of Medical Systems, Journal Year: 2024, Volume and Issue: 48(1)
Published: Feb. 17, 2024
Large Language Models (LLMs) such as General Pretrained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT), which use transformer model architectures, have significantly advanced artificial intelligence natural language processing. Recognized for their ability to capture associative relationships between words based on shared context, these models are poised transform healthcare by improving diagnostic accuracy, tailoring treatment plans, predicting patient outcomes. However, there multiple risks potentially unintended consequences associated with in applications. This study, conducted 28 participants using a qualitative approach, explores the benefits, shortcomings, of healthcare. It analyses responses seven open-ended questions simplified thematic analysis. Our research reveals including improved operational efficiency, optimized processes refined clinical documentation. Despite significant concerns about introduction bias, auditability issues privacy risks. Challenges include need specialized expertise, emergence ethical dilemmas potential reduction human element care. For medical profession, impact employment, changes patient-doctor dynamic, extensive training both system operation data interpretation.
Language: Английский
Citations
23
Pain and Therapy, Journal Year: 2024, Volume and Issue: 13(3), P. 293 - 317
Published: March 2, 2024
Pain is a significant health issue, and pain assessment essential for proper diagnosis, follow-up, effective management of pain. The conventional methods often suffer from subjectivity variability. main issue to understand better how people experience In recent years, artificial intelligence (AI) has been playing growing role in improving clinical diagnosis decision-making. application AI offers promising opportunities improve the accuracy efficiency assessment. This review article provides an overview current state explores its potential accuracy, efficiency, personalized care. By examining existing literature, research gaps, future directions, this aims guide further advancements field management. An online database search was conducted via multiple websites identify relevant articles. inclusion criteria were English articles published between January 2014 2024). Articles that available as full text trials, observational studies, articles, systemic reviews, meta-analyses included review. exclusion not language, free text, those involving pediatric patients, case reports, editorials. A total (47) conclusion, could present solutions can potentially increase precision, objective
Language: Английский
Citations
23
Humanities and Social Sciences Communications, Journal Year: 2024, Volume and Issue: 11(1)
Published: March 15, 2024
Abstract The purpose of this research is to identify and evaluate the technical, ethical regulatory challenges related use Artificial Intelligence (AI) in healthcare. potential applications AI healthcare seem limitless vary their nature scope, ranging from privacy, research, informed consent, patient autonomy, accountability, health equity, fairness, AI-based diagnostic algorithms care management through automation for specific manual activities reduce paperwork human error. main faced by states regulating were identified, especially legal voids complexities adequate regulation better transparency. A few recommendations made protect data, mitigate risks regulate more efficiently international cooperation adoption harmonized standards under World Health Organization (WHO) line with its constitutional mandate digital public health. European Union (EU) law can serve as a model guidance WHO reform International Regulations (IHR).
Language: Английский
Citations
23
Lab on a Chip, Journal Year: 2024, Volume and Issue: 24(7), P. 1833 - 1866
Published: Jan. 1, 2024
Wearable devices are increasingly popular in health monitoring, diagnosis, and drug delivery. Advances allow real-time analysis of biofluids like sweat, tears, saliva, wound fluid, urine.
Language: Английский
Citations
22