ReviewSensors (Basel, Switzerland)2024
AI-Driven Sensing Technology: Review.
Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Graphene cellulose hybrids for biodegradable flexible sensing devices.Discover nano · 2026Review
- Synthetic Expansion of Blood Dielectric Spectra at Microwave Frequencies Using Data-Driven Methods.Sensors (Basel, Switzerland) · 2026Article
- Toward Intelligent Sensing Systems: Non-Equilibrium Materials as Platforms for AI-Enabled Autonomous Discovery.Sensors (Basel, Switzerland) · 2026Article
- AI Methods in Sensor Calibration.Sensors (Basel, Switzerland) · 2026Review
- Convergence of Multidimensional Sensing: A Review of AI-Enhanced Space-Division Multiplexing in Optical Fiber Sensors.Sensors (Basel, Switzerland) · 2026Review
- Improving Clinical Diagnostics and Patient Care through Artificial Intelligence and Biosensor Technologies.ACS omega · 2026Review
- Exercise-Based Mechanotherapy: From Biomechanical Principles and Mechanotransduction to Precision Regenerative Rehabilitation.International journal of molecular sciences · 2026Review
- Predicting the Lifespan of Twisted String Actuators Using Empirical and Hybrid Machine Learning Approaches.Sensors (Basel, Switzerland) · 2025Article
- Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19.Biosensors · 2025Review
- Review
- Recent advances in medical gas sensing with artificial intelligence-enabled technology.Medical gas research · 2025Review
- Advanced Morphological and Material Engineering for High-Performance Interfacial Iontronic Pressure Sensors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- Bioelectricity harvesting from microorganism: review of recent advancements in utilizing the bioelectric properties of fungi for powering small-scale robotic systems.Frontiers in fungal biology · 2025Review
- Comprehensive Symptom Prediction in Inpatients With Acute Psychiatric Disorders Using Wearable-Based Deep Learning Models: Development and Validation Study.Journal of medical Internet research · 2024Article
- Advancements and Applications of Micro and Nanostructured Capacitive Sensors: A Review.Sensors and actuators. A, Physical · 2024Article
- Towards Automatic Object Detection and Activity Recognition in Indoor Climbing.Sensors (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Machine learning and deep learning technologies are rapidly advancing the capabilities of sensing technologies, bringing about significant improvements in accuracy, sensitivity, and adaptability. These advancements are making a notable impact across a broad spectrum of fields, including industrial automation, robotics, biomedical engineering, and civil infrastructure monitoring. The core of this transformative shift lies in the integration of artificial intelligence (AI) with sensor technology, focusing on the development of efficient algorithms that drive both device performance enhancements and novel applications in various biomedical and engineering fields. This review delves into the fusion of ML/DL algorithms with sensor technologies, shedding light on their profound impact on sensor design, calibration and compensation, object recognition, and behavior prediction. Through a series of exemplary applications, the review showcases the potential of AI algorithms to significantly upgrade sensor functionalities and widen their application range. Moreover, it addresses the challenges encountered in exploiting these technologies for sensing applications and offers insights into future trends and potential advancements.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.