Evidence map›Paper›PMID 37406117›Full record

ArticleScience advances2023

Physically defined long-term and short-term synapses for the development of reconfigurable analog-type operators capable of performing health care tasks.

Yongsuk Choi, Dong Hae Ho, Seongchan Kim, Young Jin Choi, Dong Gue Roe, In Cheol Kwak, Jihong Min, Hong Han, Wei Gao, Jeong Ho Cho

Abstract read
In one paragraph

Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. The Role of Ionic Liquids at the Biological Interfaces in Bioelectronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  3. Ferroelectric Devices for In-Memory and In-Sensor Computing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Bio-Inspired Neuromorphic Sensory Systems from Intelligent Perception to Nervetronics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  15. Review
  16. Article
  17. Article
  18. 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

10 authors.

Yongsuk ChoiAndrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.ORCID 0000-0002-9300-9068
Dong Hae HoMechanical Engineering, Soft Materials and Structures Lab, Virginia Tech, Blacksburg, VA 24061, USA.ORCID 0000-0001-7482-0173
Seongchan KimSKKU Advanced Institute of Nanotechnology (SAINT), Sungkyunkwan University, Suwon 16419, Korea.ORCID 0000-0003-3864-4250
Young Jin ChoiDepartment of Chemical and Biomolecular Engineering, Yonsei University, Seoul 03722, Republic of Korea.ORCID 0000-0002-8893-0848
Dong Gue RoeSchool of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea.ORCID 0000-0002-2889-3379
In Cheol KwakDepartment of Chemical and Biomolecular Engineering, Yonsei University, Seoul 03722, Republic of Korea.
Jihong MinAndrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.ORCID 0000-0002-5788-1473
Hong HanAndrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.ORCID 0000-0002-2852-8662
Wei GaoAndrew and Peggy Cherng Department of Medical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.ORCID 0000-0002-8503-4562
Jeong Ho ChoDepartment of Chemical and Biomolecular Engineering, Yonsei University, Seoul 03722, Republic of Korea.ORCID 0000-0002-1030-9920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracting valuable information from the overflowing data is a critical yet challenging task. Dealing with high volumes of biometric data, which are often unstructured, nonstatic, and ambiguous, requires extensive computer resources and data specialists. Emerging neuromorphic computing technologies that mimic the data processing properties of biological neural networks offer a promising solution for handling overflowing data. Here, the development of an electrolyte-gated organic transistor featuring a selective transition from short-term to long-term plasticity of the biological synapse is presented. The memory behaviors of the synaptic device were precisely modulated by restricting ion penetration through an organic channel via photochemical reactions of the cross-linking molecules. Furthermore, the applicability of the memory-controlled synaptic device was verified by constructing a reconfigurable synaptic logic gate for implementing a medical algorithm without further weight-update process. Last, the presented neuromorphic device demonstrated feasibility to handle biometric information with various update periods and perform health care tasks.

Indexed as

Neural Networks, ComputerSynapses

Identifiers

PMID37406117
PMCPMC10321737

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.