Опубликована: Окт. 18, 2024
Язык: Английский
Expert Opinion on Drug Delivery, Год журнала: 2024, Номер unknown
Опубликована: Дек. 8, 2024
Applying artificial intelligence (AI) to nanomedicine has greatly increased the production of specially engineered nanoscale materials for tailored medicine, marking a significant advancement in healthcare. With use AI, researchers can search through massive databases and find nano-properties that support range therapeutic objectives, eventually producing safer, customized nanomaterials. AI analyzes patient data, including clinical genetic information, predict results individualized care makes recommendations therapy improvement. Furthermore, logically creates nanocarriers give precise controlled drug release patterns optimize advantages minimize undesirable side effects. Even though lot potential nanomedicine, there are still issues data integration techniques, moral dilemmas, requirement governmental backing. Future developments tools multidisciplinary cooperation between scientists with expertise biological sciences nanoengineering essential nanomedicine. Together, these disciplines propel advancements precision contributing ultimate objective—a future which combine provide really The authors this editorial encourage call on scientists, physicians, legislators acknowledge its transform treatment.
Язык: Английский
Процитировано
9
Biosensors, Год журнала: 2025, Номер 15(2), С. 119 - 119
Опубликована: Фев. 18, 2025
This review into recent advancements in silicon-based technology, with a particular emphasis on the biomedical applications of silicon sensors. Owing to their diminutive size, high sensitivity, and intrinsic compatibility electronic systems, sensors have found widespread utilization across healthcare, industrial, environmental monitoring domains. In realm sensing, has demonstrated significant potential enhance human health outcomes while simultaneously driving progress microfabrication techniques for multifunctional device development. The systematically examines versatile roles fabrication electrodes, sensing channels, substrates. Silicon electrodes are widely used electrochemical biosensors glucose neural activity recording, channels field-effect transistor enable detection cancer biomarkers small molecules. Porous substrates applied optical label-free protein pathogen detection. Key challenges this field, including interaction biomolecules, economic barriers miniaturization, issues related signal stability, critically analyzed. Proposed strategies address these improve sensor functionality reliability also discussed. Furthermore, article explores emerging developments biosensors, particularly integration wearable technologies. pivotal role artificial intelligence (AI) enhancing performance, functionality, real-time capabilities is highlighted. provides comprehensive overview current state, challenges, future directions field
Язык: Английский
Процитировано
1
Journal of Personalized Medicine, Год журнала: 2024, Номер 14(11), С. 1088 - 1088
Опубликована: Ноя. 1, 2024
Artificial intelligence (AI) techniques offer great potential to advance point-of-care testing (POCT) and wearable sensors for personalized medicine applications. This review explores the recent advances transformative of use AI in improving wearables POCT. The integration significantly contributes empowering these tools enables continuous monitoring, real-time analysis, rapid diagnostics, thus enhancing patient outcomes healthcare efficiency. Wearable powered by models tremendous opportunities precise non-invasive tracking physiological conditions that are essential early disease detection treatments. AI-empowered POCT facilitates rapid, accurate making medical kits accessible available even resource-limited settings. discusses key applications data processing, sensor fusion, multivariate analytics, highlighting case examples exhibit their impact different scenarios. In addition, challenges associated with privacy, regulatory approvals, technology integrations into existing system have been overviewed. outlook emphasizes urgent need continued innovation AI-driven health technologies overcome fully achieve revolutionize medicine.
Язык: Английский
Процитировано
5
Heliyon, Год журнала: 2024, Номер 11(1), С. e41465 - e41465
Опубликована: Дек. 24, 2024
Язык: Английский
Процитировано
4
Biosensors and Bioelectronics X, Год журнала: 2025, Номер unknown, С. 100587 - 100587
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Langmuir, Год журнала: 2025, Номер unknown
Опубликована: Фев. 5, 2025
The detection of carbohydrate antigen 19–9 (CA199), a critical biomarker for pancreatic, colorectal, and gastric cancers, is essential early diagnosis disease monitoring. Traditional antibody-based assays CA199 are limited by high costs, time-consuming procedures, susceptibility to nonspecific interference. This study presents an electrochemical biosensor based on multifunctional poly(EDOT-PyBA-co-EDOT-PEG) copolymer designed overcome these limitations. integrates pyridylboronic acid (PyBA) moieties specific recognition sialic residues poly(ethylene glycol) (PEG) chains antifouling properties within conductive PEDOT framework. By eliminating antibody dependency, the reduces enhances stability, simplifies diagnostic process. Surface characterization confirmed successful incorporation PyBA PEG units, while impedance spectroscopy enabled sensitive with limit 0.05 U·mL–1 linear response range from 40 U·mL–1. Recovery tests in spiked human serum samples demonstrated excellent accuracy (97–109% recovery), validating biosensor's reliability complex biological matrices. rationally provides both sensitivity specificity maintaining resistance biofouling samples. work establishes scalable, cost-effective platform glycoprotein detection, advancing field clinical diagnostics cancer
Язык: Английский
Процитировано
0
European Journal of Orthopaedic Surgery & Traumatology, Год журнала: 2025, Номер 35(1)
Опубликована: Фев. 12, 2025
Язык: Английский
Процитировано
0
Bioelectrochemistry, Год журнала: 2025, Номер 165, С. 108948 - 108948
Опубликована: Фев. 21, 2025
Язык: Английский
Процитировано
0
Academic Pathology, Год журнала: 2025, Номер 12(1), С. 100166 - 100166
Опубликована: Янв. 1, 2025
The integration of artificial intelligence in pathology has ignited discussions about the role technology diagnostics-whether serves as a tool for augmentation or risks replacing human expertise. This manuscript explores intelligence's evolving contributions to pathology, emphasizing its potential capacity enhance, rather than eclipse, pathologist's role. Through historical comparisons, such transition from analog digital radiology, this paper highlights how technological advancements have historically expanded professional capabilities without diminishing essential element. Current applications pathology-from diagnostic standardization workflow efficiency-demonstrate augment accuracy, expedite processes, and improve consistency across institutions. However, challenges remain algorithmic bias, regulatory oversight, maintaining interpretive skills among pathologists. discussion underscores importance comprehensive governance frameworks, educational curricula, public engagement initiatives ensure remains collaborative endeavor that empowers professionals, upholds ethical standards, enhances patient outcomes. ultimately advocates balanced approach where expertise work concert advance future medicine.
Язык: Английский
Процитировано
0
ACS Sensors, Год журнала: 2025, Номер unknown
Опубликована: Март 10, 2025
Breath sensors represent a frontier in noninvasive diagnostics, leveraging the detection of volatile organic compounds (VOCs) exhaled breath for real-time health monitoring. This review highlights recent advancements breath-sensing technologies, with focus on innovative materials driving their enhanced sensitivity and selectivity. Polymers, carbon-based like graphene carbon nanotubes, metal oxides such as ZnO SnO2 have demonstrated significant potential detecting biomarkers related to diseases including diabetes, liver/kidney dysfunction, asthma, gut health. The structural operational principles these are examined, revealing how unique properties contribute key respiratory gases acetone, ammonia (NH3), hydrogen sulfide, nitric oxide. complexity samples is addressed through integration machine learning (ML) algorithms, convolutional neural networks (CNNs) support vector machines (SVMs), which optimize data interpretation diagnostic accuracy. In addition sensing VOCs, devices capable monitoring parameters airflow, temperature, humidity, essential comprehensive analysis. also explores expanding role artificial intelligence (AI) transforming wearable into sophisticated tools personalized enabling disease Together, advances sensor ML-based analytics present promising platform future individualized, healthcare.
Язык: Английский
Процитировано
0