Artificial Intelligence in Pharmaceutical Technology and Drug Delivery Design

Pharmaceutics, Journal Year: 2023, Volume and Issue: 15(7), P. 1916 - 1916

Published: July 10, 2023

Artificial intelligence (AI) has emerged as a powerful tool that harnesses anthropomorphic knowledge and provides expedited solutions to complex challenges. Remarkable advancements in AI technology machine learning present transformative opportunity the drug discovery, formulation, testing of pharmaceutical dosage forms. By utilizing algorithms analyze extensive biological data, including genomics proteomics, researchers can identify disease-associated targets predict their interactions with potential candidates. This enables more efficient targeted approach thereby increasing likelihood successful approvals. Furthermore, contribute reducing development costs by optimizing research processes. Machine assist experimental design pharmacokinetics toxicity capability prioritization optimization lead compounds, need for costly animal testing. Personalized medicine approaches be facilitated through real-world patient leading effective treatment outcomes improved adherence. comprehensive review explores wide-ranging applications delivery form designs, process optimization, testing, pharmacokinetics/pharmacodynamics (PK/PD) studies. an overview various AI-based utilized technology, highlighting benefits drawbacks. Nevertheless, continued investment exploration industry offer exciting prospects enhancing processes care.

Language: Английский

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Using artificial intelligence to improve public health: a narrative review

Frontiers in Public Health, Journal Year: 2023, Volume and Issue: 11

Published: Oct. 26, 2023

Artificial intelligence (AI) is a rapidly evolving tool revolutionizing many aspects of healthcare. AI has been predominantly employed in medicine and healthcare administration. However, public health, the widespread employment only began recently, with advent COVID-19. This review examines advances health potential challenges that lie ahead. Some ways aided delivery are via spatial modeling, risk prediction, misinformation control, surveillance, disease forecasting, pandemic/epidemic diagnosis. implementation not universal due to factors including limited infrastructure, lack technical understanding, data paucity, ethical/privacy issues.

Language: Английский

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Enhancing mental health with Artificial Intelligence: Current trends and future prospects

Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 3, P. 100099 - 100099

Published: April 17, 2024

Artificial Intelligence (AI) has emerged as a transformative force in various fields, and its application mental healthcare is no exception. Hence, this review explores the integration of AI into healthcare, elucidating current trends, ethical considerations, future directions dynamic field. This encompassed recent studies, examples applications, considerations shaping Additionally, regulatory frameworks trends research development were analyzed. We comprehensively searched four databases (PubMed, IEEE Xplore, PsycINFO, Google Scholar). The inclusion criteria papers published peer-reviewed journals, conference proceedings, or reputable online databases, that specifically focus on field offer comprehensive overview, analysis, existing literature English language. Current reveal AI's potential, with applications such early detection health disorders, personalized treatment plans, AI-driven virtual therapists. However, these advancements are accompanied by challenges concerning privacy, bias mitigation, preservation human element therapy. Future emphasize need for clear frameworks, transparent validation models, continuous efforts. Integrating therapy represents promising frontier healthcare. While holds potential to revolutionize responsible implementation essential. By addressing thoughtfully, we may effectively utilize enhance accessibility, efficacy, ethicality thereby helping both individuals communities.

Language: Английский

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Ethical Considerations in the Use of Artificial Intelligence and Machine Learning in Health Care: A Comprehensive Review

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: June 15, 2024

Artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing health care by offering unprecedented opportunities to enhance patient care, optimize clinical workflows, advance medical research. However, the integration of AI ML into healthcare systems raises significant ethical considerations that must be carefully addressed ensure responsible equitable deployment. This comprehensive review explored multifaceted surrounding use in including privacy data security, algorithmic bias, transparency, validation, professional responsibility. By critically examining these dimensions, stakeholders can navigate complexities while safeguarding welfare upholding principles. embracing best practices fostering collaboration across interdisciplinary teams, community harness full potential usher a new era personalized data-driven prioritizes well-being equity.

Language: Английский

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Artificial intelligence in healthcare delivery: Prospects and pitfalls

Journal of Medicine Surgery and Public Health, Journal Year: 2024, Volume and Issue: 3, P. 100108 - 100108

Published: April 16, 2024

This review provides a comprehensive examination of the integration Artificial Intelligence (AI) into healthcare, focusing on its transformative implications and challenges. Utilising systematic search strategy across electronic databases such as PubMed, Scopus, Embase, Sciencedirect, relevant peer-reviewed articles published in English between January 2010 till date were identified. Findings reveal AI's significant impact healthcare delivery, including role enhancing diagnostic precision, enabling treatment personalisation, facilitating predictive analytics, automating tasks, driving robotics. AI algorithms demonstrate high accuracy analysing medical images for disease diagnosis enable creation tailored plans based patient data analysis. Predictive analytics identify high-risk patients proactive interventions, while AI-powered tools streamline workflows, improving efficiency experience. Additionally, AI-driven robotics automate tasks enhance care particularly rehabilitation surgery. However, challenges quality, interpretability, bias, regulatory frameworks must be addressed responsible implementation. Recommendations emphasise need robust ethical legal frameworks, human-AI collaboration, safety validation, education, regulation to ensure effective healthcare. valuable insights potential advocating implementation efficacy.

Language: Английский

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Ethical Considerations in Artificial Intelligence Interventions for Mental Health and Well-Being: Ensuring Responsible Implementation and Impact

Social Sciences, Journal Year: 2024, Volume and Issue: 13(7), P. 381 - 381

Published: July 22, 2024

AI has the potential to revolutionize mental health services by providing personalized support and improving accessibility. However, it is crucial address ethical concerns ensure responsible beneficial outcomes for individuals. This systematic review examines considerations surrounding implementation impact of artificial intelligence (AI) interventions in field well-being. To a comprehensive analysis, we employed structured search strategy across top academic databases, including PubMed, PsycINFO, Web Science, Scopus. The scope encompassed articles published from 2014 2024, resulting 51 relevant articles. identifies 18 key considerations, 6 associated with using wellbeing (privacy confidentiality, informed consent, bias fairness, transparency accountability, autonomy human agency, safety efficacy); 5 principles development technologies settings practice positive (ethical framework, stakeholder engagement, review, mitigation, continuous evaluation improvement); 7 practices, guidelines, recommendations promoting use (adhere transparency, prioritize data privacy security, mitigate involve stakeholders, conduct regular reviews, monitor evaluate outcomes). highlights importance By addressing privacy, bias, oversight, evaluation, can that like chatbots AI-enabled medical devices are developed deployed an ethically sound manner, respecting individual rights, maximizing benefits while minimizing harm.

Language: Английский

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Navigating the Future: The Transformative Impact of Artificial Intelligence on Hospital Management- A Comprehensive Review

Cureus, Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 20, 2024

This comprehensive review explores the transformative impact of artificial intelligence (AI) on hospital management, delving into its applications, challenges, and future trends. Integrating AI in administrative functions, clinical operations, patient engagement holds significant promise for enhancing efficiency, optimizing resource allocation, revolutionizing care. However, this evolution is accompanied by ethical, legal, operational considerations that necessitate careful navigation. The underscores key findings, emphasizing implications management. It calls a proactive approach, urging stakeholders to invest education, prioritize ethical guidelines, foster collaboration, advocate thoughtful regulation, embrace culture innovation. healthcare industry can successfully navigate era through collective action, ensuring contributes more effective, accessible, patient-centered delivery.

Language: Английский

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Patient perspectives on informed consent for medical AI: A web-based experiment

Digital Health, Journal Year: 2024, Volume and Issue: 10

Published: Jan. 1, 2024

Objective Despite the increasing use of AI applications as a clinical decision support tool in healthcare, patients are often unaware their physician's decision-making process. This study aims to determine whether doctors should disclose tools diagnosis and what kind information be provided. Methods A survey experiment with 1000 respondents South Korea was conducted estimate patients’ perceived importance regarding an deciding receive treatment. Results The found that increases related its use, compared when physician consults human radiologist. Information is used by participants either more important than or similar regularly disclosed short-term effects not used. Further analysis revealed gender, age, income have statistically significant effect on every piece information. Conclusions supports disclosure during informed consent However, tailored individual patient's needs, patient preferences for vary across age levels. It recommended ethical guidelines developed using diagnoses go beyond mere legal requirements.

Language: Английский

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A trustworthy AI reality-check: the lack of transparency of artificial intelligence products in healthcare

Frontiers in Digital Health, Journal Year: 2024, Volume and Issue: 6

Published: Feb. 20, 2024

Trustworthy medical AI requires transparency about the development and testing of underlying algorithms to identify biases communicate potential risks harm. Abundant guidance exists on how achieve for products, but it is unclear whether publicly available information adequately informs their risks. To assess this, we retrieved public documentation 14 CE-certified AI-based radiology products II b risk category in EU from vendor websites, scientific publications, European EUDAMED database. Using a self-designed survey, reported development, validation, ethical considerations, deployment caveats, according trustworthy guidelines. We scored each question with either 0, 0.5, or 1, rate if required was “unavailable”, “partially available,” “fully available.” The product calculated relative all 55 questions. Transparency scores ranged 6.4% 60.9%, median 29.1%. Major gaps included missing training data, limitations deployment. Ethical aspects like consent, safety monitoring, GDPR-compliance were rarely documented. Furthermore, caveats different demographics settings scarce. In conclusion, authorized Europe lacks sufficient inform call lawmakers regulators establish legally mandated requirements substantive fulfill promise health.

Language: Английский

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Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications

Journal of Clinical Medicine, Journal Year: 2025, Volume and Issue: 14(2), P. 550 - 550

Published: Jan. 16, 2025

The convergence of Artificial Intelligence (AI) and neuroscience is redefining our understanding the brain, unlocking new possibilities in research, diagnosis, therapy. This review explores how AI’s cutting-edge algorithms—ranging from deep learning to neuromorphic computing—are revolutionizing by enabling analysis complex neural datasets, neuroimaging electrophysiology genomic profiling. These advancements are transforming early detection neurological disorders, enhancing brain–computer interfaces, driving personalized medicine, paving way for more precise adaptive treatments. Beyond applications, itself has inspired AI innovations, with architectures brain-like processes shaping advances algorithms explainable models. bidirectional exchange fueled breakthroughs such as dynamic connectivity mapping, real-time decoding, closed-loop systems that adaptively respond states. However, challenges persist, including issues data integration, ethical considerations, “black-box” nature many systems, underscoring need transparent, equitable, interdisciplinary approaches. By synthesizing latest identifying future opportunities, this charts a path forward integration neuroscience. From harnessing multimodal cognitive augmentation, fusion these fields not just brain science, it reimagining human potential. partnership promises where mysteries unlocked, offering unprecedented healthcare, technology, beyond.

Language: Английский

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