Evidence map›Paper›PMID 37622898›Full record

ReviewBiosensors2023

Application of Intelligent Medical Sensing Technology.

Jie Fu, Qiya Gao, Shuang Li

Open access · goldAbstract readReview
In one paragraph

Review in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
17.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 14 citations in OpenAlex.

  1. AI Methods in Sensor Calibration.Sensors (Basel, Switzerland) · 2026
    Review
  2. Review
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Jie FuAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.
Qiya GaoAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.
Shuang LiAcademy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin 300072, China.ORCID 0000-0002-3483-5087
Tianjin University · CN

Funding

HongKong Scholars Program XJ2021034National Key Research and Development Program of China 2022YFF1202700National Natural Science Foundation of China 82001922
6 · The paper itself

Abstract

With the popularization of intelligent sensing and the improvement of modern medical technology, intelligent medical sensing technology has emerged as the times require. This technology combines basic disciplines such as physics, mathematics, and materials with modern technologies such as semiconductors, integrated circuits, and artificial intelligence, and has become one of the most promising in the medical field. The core of intelligent medical sensor technology is to make existing medical sensors intelligent, portable, and wearable with full consideration of ergonomics and sensor power consumption issues in order to conform to the current trends in cloud medicine, personalized medicine, and health monitoring. With the development of automation and intelligence in measurement and control systems, it is required that sensors have high accuracy, reliability, and stability, as well as certain data processing capabilities, self-checking, self-calibration, and self-compensation, while traditional medical sensors cannot meet such requirements. In addition, to manufacture high-performance sensors, it is also difficult to improve the material process alone, and it is necessary to combine computer technology with sensor technology to make up for its performance shortcomings. Intelligent medical sensing technology combines medical sensors with microprocessors to produce powerful intelligent medical sensors. Based on the original sensor functions, intelligent medical sensors also have functions such as self-compensation, self-calibration, self-diagnosis, numerical processing, two-way communication, information storage, and digital output. This review focuses on the application of intelligent medical sensing technology in biomedical sensing detection from three aspects: physical sensor, chemical sensor, and biosensor.

Indexed as

Artificial IntelligenceIntelligenceAutomationPrecision MedicineReproducibility of Resultsbiosensorchemical sensorhealth monitoringintegrated circuitsintelligent medical sensing technologyphysical sensor

Identifiers

PMID37622898
PMCPMC10452530
OpenAlexW4385812799

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.