Microchimica Acta, Год журнала: 2024, Номер 191(11)
Опубликована: Окт. 15, 2024
Язык: Английский
Materials Today Sustainability, Год журнала: 2024, Номер unknown, С. 101068 - 101068
Опубликована: Дек. 1, 2024
Язык: Английский
Процитировано
8
Journal of The Electrochemical Society, Год журнала: 2024, Номер 171(9), С. 097503 - 097503
Опубликована: Авг. 5, 2024
The burgeoning intersection of machine learning (ML) with electrochemical sensing heralds a transformative era in analytical science, pushing the boundaries what’s possible detecting and quantifying chemical substances unprecedented precision efficiency. This convergence has accelerated number discoveries, improving sensors’ sensitivity, selectivity, ability to comprehend complicated data streams real-time. Such advancements are crucial across various applications, from monitoring health biomarkers environmental pollutants ensuring industrial safety. Yet, this integration is not without its challenges; it necessitates navigating intricate ethical considerations around use, robust privacy measures, developing specialized software tools that balance accessibility security. As field progresses, addressing these challenges head-on essential for harnessing full potential ML-enhanced sensing. review briefly explores dimensions, spotlighting significant technological strides, landscape, dynamic interplay between open-source proprietary solutions while also casting forward gaze at promising future directions interdisciplinary venture.
Язык: Английский
Процитировано
6
Electrochimica Acta, Год журнала: 2023, Номер 475, С. 143664 - 143664
Опубликована: Дек. 13, 2023
Язык: Английский
Процитировано
12
Environmental Research, Год журнала: 2024, Номер 262, С. 119801 - 119801
Опубликована: Авг. 13, 2024
Язык: Английский
Процитировано
4
Journal of Pharmaceutical and Biomedical Analysis Open, Год журнала: 2024, Номер 4, С. 100041 - 100041
Опубликована: Сен. 6, 2024
Язык: Английский
Процитировано
4
Advanced Engineering Materials, Год журнала: 2024, Номер unknown
Опубликована: Сен. 8, 2024
Recent advancements in artificial intelligence (AI) technologies, particularly machine learning (ML) techniques, have opened up a promising frontier the development of intelligent soft bioelectronics, demonstrating unparalleled performance interfacing with human body. Hydrogels, owing to their unique combination biocompatibility, tunable mechanical properties, and high water content, emerged as versatile platform for constructing bioelectronic devices. Functionalized hydrogels, such conductive can efficiently capture biosignals from various target tissues while seamlessly forming conformal reliable interfaces. They also function an intermediary layer between biological bioelectronics diagnosis therapy purposes. Meanwhile, ML has demonstrated its efficacy processing extensive datasets collected bioelectronics. The convergence hydrogel‐based unlocked myriad possibilities unprecedented diagnostics, therapeutics, beyond. In this review, latest advances are introduced. After briefly describing materials device strategies high‐performance hydrogel how be integrated augment functionalities is discussed. examples ML‐integrated then Finally, review concluded by introducing future potential applications AI alongside inherent challenges interdisciplinary domain.
Язык: Английский
Процитировано
4
Advanced Sensor Research, Год журнала: 2025, Номер unknown
Опубликована: Янв. 23, 2025
Abstract Biorecognition elements immobilized into nanopores have transformed point‐of‐care (POC) diagnostics by converting molecular interactions electrical and fluorescent signals.This study introduces Bio‐Sensei, a high‐throughput screening (HTS) microfluidic platform based on nanopore biosensing. Integrating robotic sampler, electrochemical, fluorescence setup, Bio‐Sensei operates as an Internet of Things (IoT) with integrated data analysis. The platform's utility is demonstrated functionalized amino terminal Cu(II)‐ Ni(II)‐binding (ATCUN) peptide ion track‐etched membrane. Automated testing atchieves significantly higher F‐stat value than the critical treshold, while unsupervised clustering reveals optimalnanopores pore size. biosensordemonstrates remarkable stability, selectivity, sensitivity detection limits 10 −6 using −15 Musing cyclic voltammetry measurements. Combining these methods enhances machine learning models for Cu 2+ concentration prediction, achieving receiver operating characteristic area under curve values exceeding 95%.
Язык: Английский
Процитировано
0
Sensing and Bio-Sensing Research, Год журнала: 2025, Номер unknown, С. 100771 - 100771
Опубликована: Фев. 1, 2025
Язык: Английский
Процитировано
0
Sensors, Год журнала: 2025, Номер 25(5), С. 1367 - 1367
Опубликована: Фев. 23, 2025
Wearable sensors have appeared as a promising solution for real-time, non-invasive monitoring in diverse fields, including healthcare, environmental sensing, and wearable electronics. Surface-enhanced Raman spectroscopy (SERS)-based leverage the unique properties of SERS, such plasmonic signal enhancement, high molecular specificity, potential single-molecule detection, to detect identify wide range analytes with ultra-high sensitivity selectivity. However, it is important note that utilize various sensing mechanisms, not all rely on SERS technology, their design depends specific application. This comprehensive review highlights recent trends advancements technologies, focusing design, fabrication, integration into practical devices. Key innovations material selection, use nanomaterials flexible substrates, significantly enhanced sensor performance wearability. Moreover, we discuss challenges miniaturization, power consumption, long-term stability, along solutions address these issues. Finally, outlook technologies presented, emphasizing need interdisciplinary research drive next generation smart wearables capable real-time health diagnostics, monitoring, beyond.
Язык: Английский
Процитировано
0
TrAC Trends in Analytical Chemistry, Год журнала: 2025, Номер 187, С. 118196 - 118196
Опубликована: Фев. 27, 2025
Язык: Английский
Процитировано
0