AI-Optimized Electrochemical Aptasensors for Stable, Reproducible Detection of Neurodegenerative Diseases, Cancer, and Coronavirus DOI Creative Commons
Amira Elsir Tayfour Ahmed,

Th. S. Dhahi,

Tahani A. Attia

и другие.

Heliyon, Год журнала: 2024, Номер 11(1), С. e41338 - e41338

Опубликована: Дек. 18, 2024

AI-optimized electrochemical aptasensors are transforming diagnostic testing by offering high sensitivity, selectivity, and rapid response times. Leveraging data-driven AI techniques, these sensors provide a non-invasive, cost-effective alternative to traditional methods, with applications in detecting molecular biomarkers for neurodegenerative diseases, cancer, coronavirus. The performance metrics outlined the comparative table illustrate significant advancements enabled integration. Sensitivity increases from 60 75 % ordinary 85-95 %, while specificity improves 70-80 90-98 %. This enhanced allows ultra-low detection limits, such as 10 fM carcinoembryonic antigen (CEA) 20 mucin-1 (MUC1) using Electrochemical Impedance Spectroscopy (EIS), 1 pM prostate-specific (PSA) Differential Pulse Voltammetry (DPV). Similarly, Square Wave (SWV) potentiometric have detected alpha-fetoprotein (AFP) at 5 epithelial cell adhesion molecule (EpCAM) 100 fM, respectively. integration also enhances reproducibility, reduces false positives negatives (from 15-20 5-10 %), significantly decreases times 10-15 s 2-3 s). These improve data processing speeds min per sample 2-5 min) calibration accuracy (<2 margin of error compared expanding application scope multi-target biomarker detection. review highlights how position powerful tools personalized treatment, point-of-care testing, continuous health monitoring. Despite higher cost ($500-$1,500/unit), their portability promise revolutionize healthcare, environmental monitoring, food safety, ultimately improving public outcomes.

Язык: Английский

A Review of Biosensors and Artificial Intelligence in Healthcare and their Clinical Significance DOI Open Access

Mehtab Tariq

Psychology & Psychological Research International Journal, Год журнала: 2024, Номер 9(1), С. 1 - 23

Опубликована: Янв. 1, 2024

In the past decade, a substantial increase in medical data from various sources, including wearable sensors, imaging, personal health records, and public organizations, has propelled advancements sciences. The evolution of computational hardware, such as cloud computing, GPUs, FPGAs, TPUs, enabled effective utilization this vast amount data. Consequently, sophisticated AI techniques have been developed to extract valuable insights healthcare datasets. This article provides comprehensive overview recent developments biosensors within life review highlights role machine learning key areas precision medicine, designed for Internet Things (IoT). Emphasis is placed on latest progress biosensing technologies, where plays pivotal monitoring electro-physiological electro-chemical signals aiding disease diagnosis. These underscore growing trend towards personalized offering precise costefficient point-of-care treatment. Additionally, delves into computing accelerated AI, edge federated specifically tailored challenges associated with data-driven approaches, potential issues arising IoT-based healthcare, distribution shifts among different modalities are thoroughly explored. discussion concludes future prospects field.

Язык: Английский

Процитировано

3

AI-Reinforced Wearable Sensors and Intelligent Point-of-Care Tests DOI Open Access

Ghita Yammouri,

Abdellatif Ait Lahcen

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

3

AI-Optimized Electrochemical Aptasensors for Stable, Reproducible Detection of Neurodegenerative Diseases, Cancer, and Coronavirus DOI Creative Commons
Amira Elsir Tayfour Ahmed,

Th. S. Dhahi,

Tahani A. Attia

и другие.

Heliyon, Год журнала: 2024, Номер 11(1), С. e41338 - e41338

Опубликована: Дек. 18, 2024

AI-optimized electrochemical aptasensors are transforming diagnostic testing by offering high sensitivity, selectivity, and rapid response times. Leveraging data-driven AI techniques, these sensors provide a non-invasive, cost-effective alternative to traditional methods, with applications in detecting molecular biomarkers for neurodegenerative diseases, cancer, coronavirus. The performance metrics outlined the comparative table illustrate significant advancements enabled integration. Sensitivity increases from 60 75 % ordinary 85-95 %, while specificity improves 70-80 90-98 %. This enhanced allows ultra-low detection limits, such as 10 fM carcinoembryonic antigen (CEA) 20 mucin-1 (MUC1) using Electrochemical Impedance Spectroscopy (EIS), 1 pM prostate-specific (PSA) Differential Pulse Voltammetry (DPV). Similarly, Square Wave (SWV) potentiometric have detected alpha-fetoprotein (AFP) at 5 epithelial cell adhesion molecule (EpCAM) 100 fM, respectively. integration also enhances reproducibility, reduces false positives negatives (from 15-20 5-10 %), significantly decreases times 10-15 s 2-3 s). These improve data processing speeds min per sample 2-5 min) calibration accuracy (<2 margin of error compared expanding application scope multi-target biomarker detection. review highlights how position powerful tools personalized treatment, point-of-care testing, continuous health monitoring. Despite higher cost ($500-$1,500/unit), their portability promise revolutionize healthcare, environmental monitoring, food safety, ultimately improving public outcomes.

Язык: Английский

Процитировано

2