Multiscale and Multidisciplinary Modeling Experiments and Design, Год журнала: 2024, Номер 8(7)
Опубликована: Июль 1, 2024
Язык: Английский
Discover Oncology, Год журнала: 2025, Номер 16(1)
Опубликована: Янв. 22, 2025
Abstract Liver cancer is one of the most challenging malignancies, often associated with poor prognosis and limited treatment options. Recent advancements in nanotechnology artificial intelligence (AI) have opened new frontiers fight against this disease. Nanotechnology enables precise, targeted drug delivery, enhancing efficacy therapeutics while minimizing off-target effects. Simultaneously, AI contributes to improved diagnostic accuracy, predictive modeling, development personalized strategies. This review explores convergence liver treatment, evaluating current progress, identifying existing research gaps, discussing future directions. We highlight how AI-powered algorithms can optimize nanocarrier design, facilitate real-time monitoring efficacy, enhance clinical decision-making. By integrating nanotechnology, clinicians achieve more accurate patient stratification personalization, ultimately improving outcomes. holds significant promise for transforming therapy into a individualized, efficient process. However, data privacy, regulatory hurdles, need large-scale validation remain. Addressing these issues will be essential fully realizing potential technologies oncology.
Язык: Английский
Процитировано
9
Lab on a Chip, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
This review highlights recent technological advances for progress in particle manipulation under X-force fields, and forecasts the trajectory of future developments.
Язык: Английский
Процитировано
2
Nano Trends, Год журнала: 2024, Номер unknown, С. 100052 - 100052
Опубликована: Сен. 1, 2024
Язык: Английский
Процитировано
9
Advanced Intelligent Systems, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 26, 2024
Microfluidics has evolved into a transformative technology with far‐reaching applications in biomedical research. However, designing and optimizing custom microfluidic systems remains challenging because of their inherent complexities. Integrating artificial intelligence (AI) microfluidics promises to overcome these barriers by leveraging AI algorithms automate device design, streamline experimentation, enhance diagnostic therapeutic outcomes. Psoriasis is an incurable dermatological condition that difficult diagnose treat owing its complex pathogenesis. Traditional approaches are often ineffective fail address individual variabilities disease progression treatment responses. AI‐coupled platforms have the potential revolutionize psoriasis research clinical expansive applications. AI‐driven chips embedded biosensors precisely detect biomarkers (BMs), manipulate biological samples, mimic psoriasis‐like vivo vitro models, thereby allowing real‐time monitoring optimized testing. This review examines AI‐powered for advancing It design mechanisms cell screening, diagnosis, drug delivery. highlights recent advances, applications, challenges, future perspectives, ethical considerations personalized care patient
Язык: Английский
Процитировано
3
Advances in public policy and administration (APPA) book series, Год журнала: 2025, Номер unknown, С. 219 - 250
Опубликована: Янв. 24, 2025
This chapter explores the changes in security processes caused by robots used various functions different areas of public and their effects on strategy policies. The predicts may have results two perspectives. first addresses use as a tool for ensuring security, requiring an increase digital skills individuals developing capacity to adapt these technologies. second perspective considers directly replacing people's positions become employment subject. Building hybrid approach based perspectives, conveys development robot technology how are integrated into Finally, it gives case study USA, which emerges most concrete saturated example robotics developments, Türkiye, researchers, selected excellent terms both familiarity relative difference homeland.
Язык: Английский
Процитировано
0
Micromachines, Год журнала: 2025, Номер 16(3), С. 301 - 301
Опубликована: Март 4, 2025
Technological advances have allowed various systems to be developed on a small scale [...]
Язык: Английский
Процитировано
0
International Journal of Biological Macromolecules, Год журнала: 2025, Номер unknown, С. 142136 - 142136
Опубликована: Март 1, 2025
Язык: Английский
Процитировано
0
BioNanoScience, Год журнала: 2025, Номер 15(3)
Опубликована: Май 21, 2025
Язык: Английский
Процитировано
0
Inorganic Chemistry Communications, Год журнала: 2024, Номер 167, С. 112736 - 112736
Опубликована: Июнь 14, 2024
Язык: Английский
Процитировано
1
Biomicrofluidics, Год журнала: 2024, Номер 18(6)
Опубликована: Ноя. 20, 2024
Microfluidic devices have many unique practical applications across a wide range of fields, making it important to develop accurate models these devices, and different been developed. Existing modeling methods mainly include mechanism derivation semi-empirical correlations, but both are not universally applicable. In order achieve more general process, the use data-driven has studied recently. This review highlights recent advances in application techniques for simulating designing microfluidic devices. First, introduces traditional approaches microfluidics; subsequently, through database sources, reviews studies on three categories; finally, raises some open issues that require further investigation.
Язык: Английский
Процитировано
1