Evidence map›Paper›PMID 38974973›Full record

ArticleiScience2024

Optimizing biomagnetic sensor performance through

Chenxi Sun, Yike Liang, Xiao Yang, Biying Zhao, Pengju Zhang, Sirui Liu, Dongyi Yang, Teng Wu, Jianwei Zhang, Hong Guo

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Chenxi SunState Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics, and Center for Quantum Information Technology, Peking University, Beijing 100871, China.
Yike LiangSchool of Life Sciences, Peking University, Beijing 100871, China.
Xiao YangState Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics, and Center for Quantum Information Technology, Peking University, Beijing 100871, China.
Biying ZhaoState Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics, and Center for Quantum Information Technology, Peking University, Beijing 100871, China.
Pengju ZhangFaculty of Engineering, University of Bristol, Bristol BS8 1TR, UK.
Sirui LiuSchool of Physics, Peking University, Beijing 100871, China.
Dongyi YangSchool of Physics, Peking University, Beijing 100871, China.
Teng WuState Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics, and Center for Quantum Information Technology, Peking University, Beijing 100871, China.
Jianwei ZhangSchool of Physics, Peking University, Beijing 100871, China.
Hong GuoState Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics, and Center for Quantum Information Technology, Peking University, Beijing 100871, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advancing biomagnetic measurement capabilities requires a nuanced understanding of sensor performance beyond traditional metrics. This study introduces Biomagnetism Evaluation via Simulated Testing (BEST), a novel methodology combining a current dipole model simulating cardiac biomagnetic fields with a convolutional neural network. Our investigation reveals that optimal sensor array performance is achieved when sensors are in close proximity to the magnetic source, with a shorter effective domain. Contrary to common assumptions, the bottom edge length of the sensor has a negligible impact on array performance. BEST provides a versatile framework for exploring the influence of diverse technical indicators on biomagnetic sensor performance, offering valuable insights for sensor development and selection.

Indexed as

biological sciencescomputer sciencephysics

Identifiers

PMID38974973
PMCPMC11226959

What OpenQuestion holds

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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.