Evidence map›Paper›PMID 40521095›Full record

ReviewFrontiers in bioengineering and biotechnology2025

Intelligent blood collection robot: key technologies, clinical applications, and future challenges.

Yaqing Wang, Huajiang Ruan, Yaoqin Ruan, Qi Li, Chen Wang, Zhaoxi Fang

Abstract readReview
In one paragraph

Review in Frontiers in bioengineering and biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Yaqing WangDepartment of Transfusion Medicine, The Affiliated Hospital of Shaoxing University (Shaoxing Municipal Hospital), Shaoxing, China.
Huajiang RuanDepartment of Computer Science and Engineering, Shaoxing University, Shaoxing, China.
Yaoqin RuanDepartment of Transfusion Medicine, The Affiliated Hospital of Shaoxing University (Shaoxing Municipal Hospital), Shaoxing, China.
Qi LiDepartment of Computer Science and Engineering, Shaoxing University, Shaoxing, China.
Chen WangDepartment of Computer Science and Engineering, Shaoxing University, Shaoxing, China.
Zhaoxi FangDepartment of Computer Science and Engineering, Shaoxing University, Shaoxing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blood collection is one of the key steps in blood testing. The use of intelligent blood collection robots to achieve automated blood collection can effectively reduce the workload of medical staff, improve the efficiency and accuracy of blood collection, and improve the patient experience, and has received extensive attention from academic and industrial circles in recent years. This paper aims to provide a comprehensive introduction to the key technologies, latest research progress, current clinical application status, and future development opportunities and challenges of intelligent blood collection robots. The paper introduces the key technologies that can achieve autonomous blood collection, including blood vessel recognition and positioning technology, mechanical arm design, and puncture control technology. Among them, blood vessel recognition and positioning is one of the key supporting technologies for intelligent blood collection, which can be realized by using technologies such as machine vision, near-infrared imaging, and ultrasound imaging. In addition, the paper also introduces some existing commercial intelligent blood collection robots and their clinical application cases in hospitals. Finally, we analyze the future application prospects and challenges of intelligent blood collection robots.

Indexed as

clinical applicationintelligent blood collection robotmachine visionpuncture controlvascular recognition

Identifiers

PMID40521095
PMCPMC12162698

What OpenQuestion holds

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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.