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ISSN: 2957-5478
Indexed in: OAJ, Europub, CNKI, Crossref, Dimensions, Google Scholar
Editor-in-Chief: Haipo Cui
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Volume 4, Issue 1
Development of an automated cytological smear staining device for rapid on-site evaluation

Guangyan Wang1, Kai Yang1, Chunhua Zhou2, Duowu Zou2, Shiju Yan1


1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China. 

2Department of Gastroenterology, Ruijin Hospital, Shanghai 200025, China.


Address correspondence to: Shiju Yan, School of Health Science and Engineering, University of Shanghai for Science and Technology, No. 516 Jungong Road, Yangpu, Shanghai 200093, China. E-mail: yanshiju@usst.edu.cn.


DOI: https://doi.org/10.61189/599339cpncph


Received January 20, 2025; Accepted April 16, 2025; Published March 24, 2026


Highlights

● The developed device reduces manpower and time consumption, improving staining efficiency in digestive endoscopy centers. 

● It has a compact design with minimal contamination to the operating environment.  

● The developed device demonstrates excellent staining performance and has been recognized by clinicians.

Research Article |Published on: 24 March 2026

[Progress in Medical Devices] 2026; 4 (1): 1-9

DOI: https://doi.org/10.61189/599339cpncph
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AI-assisted diagnosis of myocardial hypertrophy based on cardiac MRI: A systemic review

Shimin Zhou1, Xudong Guo1,2, Yunli Shen2, Qinfen Jiang2, Xin Gong2, Jie Ding2, Yihong Yang3, Guojie Xu1, Jican Wen1, Jingyang Niu1 


1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.  

2State Key Laboratory of Cardiovascular Diseases and Medical Innovation Center, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200093, China. 

3Department of Nuclear Medicine, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.


Address correspondence to: Xudong Guo, School of Health Science and Engineering, University of Shanghai for Science and Technology, No. 516 Jungong Road, Yangpu District, Shanghai 200093, China. E-mail: guoxd@usst.edu.cn.


DOI: https://doi.org/10.61189/569607adnpiw


Received October 25, 2025; Accepted February 12, 2026; Published March 31, 2026


Highlights 

● This review systematically summarizes the research progress of artificial intelligence technologies in the diagnosis of cardiac hypertrophy based on cardiac MRI, with a focus on AI diagnostic methods utilizing Cine-MRI, T1/T2 Mapping, late gadolinium enhancement (LGE), and multi-sequence fusion strategies. 

● This review highlights the application potential and current limitations of natural language processing-based automated MRI report parsing technology for large-scale case screening and phenotypic stratification. 

● This review analyzes existing challenges in AI diagnosis, including data quality, annotation consistency, and model generalization, and discusses future directions such as multicenter collaboration, multimodal data fusion, and clinical translation.

Review Article |Published on: 31 March 2026

[Progress in Medical Devices] 2026; 4 (1): 55-65

DOI: https://doi.org/10.61189/569607adnpiw
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Slim exquisite easy-exposing video laryngoscope: A novel video laryngoscope

Letter To Editor |Published on: 31 March 2026

[Progress in Medical Devices] 2026; 4 (1): 66-67

DOI: https://doi.org/10.61189/551629zyhfiv
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