Yao‐Sian Huang

404 citations

12 papers · 288 indexed · h-index 8

Co-authors: Ruey‐Feng Chang Chiun‐Sheng Huang Rong‐Tai Chen Yeun‐Chung Chang Hsin‐Ming Chen Cher‐Wei Liang Chia‐Hung Chen Chih‐Yen Tu
Topics: Radiomics and Machine Learning in Medical Imaging (6 papers)AI in cancer detection (6 papers)Lung Cancer Diagnosis and Treatment (3 papers)
Cited by: Health Informatics Radiology, Nuclear Medicine and Imaging Neurology
Journals: IEEE Transactions on Medical Imaging Medical Physics Ultrasound in Medicine & Biology
Partner nations: Taiwan United States Japan

In The Last Decade

Yao‐Sian Huang

12 papers receiving 284 citations

Peers

Countries citing papers authored by Yao‐Sian Huang

Since Specialization

Citations

This map shows the geographic impact of Yao‐Sian Huang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yao‐Sian Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yao‐Sian Huang more than expected).

Fields of papers citing papers by Yao‐Sian Huang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yao‐Sian Huang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yao‐Sian Huang. The network helps show where Yao‐Sian Huang may publish in the future.

Co-authorship network of co-authors of Yao‐Sian Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Yao‐Sian Huang. A scholar is included among the top collaborators of Yao‐Sian Huang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yao‐Sian Huang. Yao‐Sian Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

#	Work	Indexed citations
1	Detection and Diagnosis for Pressure Injury by Using SE-Swin Cascade R-CNN 2025 ·IEEE Multimedia ·Yao‐Sian Huang,(unknown),(unknown),(unknown),(unknown),(unknown),Ruey‐Feng Chang	1
2	Machine Learning: Using Xception, a Deep Convolutional Neural Network Architecture, to Implement Pectus Excavatum Diagnostic Tool from Frontal-View Chest X-rays 2023 ·Biomedicines ·(unknown),I‐Shiang Tzeng,Yao‐Sian Huang,Yuan‐Yu Hsu,(unknown),(unknown),Yeung‐Leung Cheng	4
3	Stratifying High-Risk Thyroid Nodules Using a Novel Deep Learning System 2023 ·Experimental and Clinical Endocrinology & Diabetes ·Chia‐Po Fu,(unknown),Yao‐Sian Huang,Chiou‐Shann Fuh,Ruey‐Feng Chang	2
4	An improved 3-D attention CNN with hybrid loss and feature fusion for pulmonary nodule classification 2022 ·Computer Methods and Programs in Biomedicine ·Yao‐Sian Huang,(unknown),(unknown),Jun Zhang,Hsin‐Ming Chen,Yeun‐Chung Chang,Ruey‐Feng Chang	13
5	One-stage pulmonary nodule detection using 3-D DCNN with feature fusion and attention mechanism in CT image 2022 ·Computer Methods and Programs in Biomedicine ·Yao‐Sian Huang,(unknown),Hsin‐Ming Chen,Yeun‐Chung Chang,Ruey‐Feng Chang	35
6	3-D Res-CapsNet convolutional neural network on automated breast ultrasound tumor diagnosis 2021 ·European Journal of Radiology ·(unknown),Yao‐Sian Huang,(unknown),(unknown),Cheng‐Kuang Lee,Lixian Liu,Anhua Li,Xi Lin,Ruey‐Feng Chang	19
7	Computer-aided diagnosis of endobronchial ultrasound images using convolutional neural network 2019 ·Computer Methods and Programs in Biomedicine ·Chia‐Hung Chen,Yan‐Wei Lee,Yao‐Sian Huang,Wei‐Ren Lan,Ruey‐Feng Chang,Chih‐Yen Tu,(unknown),Wei‐Chih Liao	40
8	A computer‐aided diagnosis system for differentiation and delineation of malignant regions on whole‐slide prostate histopathology image using spatial statistics and multidimensional DenseNet 2019 ·Medical Physics ·(unknown),Yao‐Sian Huang,(unknown),Cher‐Wei Liang,Ruey‐Feng Chang	32
9	Tumor Detection in Automated Breast Ultrasound Using 3-D CNN and Prioritized Candidate Aggregation 2018 ·IEEE Transactions on Medical Imaging ·(unknown),Yao‐Sian Huang,Rong‐Tai Chen,Chiun‐Sheng Huang,Ruey‐Feng Chang	116
10	Computer-Aided tumor diagnosis in 3-D breast elastography 2017 ·Computer Methods and Programs in Biomedicine ·Yao‐Sian Huang,Etsuo Takada,(unknown),Chiun‐Sheng Huang,(unknown),Ruey‐Feng Chang	8
11	Intrinsic subtypes and tumor grades in breast cancer are associated with distinct 3-D power Doppler sonographic vascular features 2014 ·European Journal of Radiology ·Yeun‐Chung Chang,Yao‐Sian Huang,Chiun‐Sheng Huang,Jeon‐Hor Chen,Ruey‐Feng Chang	5
12	Computer-Aided Diagnosis for 3-D Power Doppler Breast Ultrasound 2013 ·Ultrasound in Medicine & Biology ·Yi‐Chen Lai,Yao‐Sian Huang,(unknown),Chui‐Mei Tiu,Yi‐Hong Chou,Ruey‐Feng Chang	13

About Yao‐Sian Huang

Yao‐Sian Huang is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Oral Surgery, having authored 12 papers that have together received 288 indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (6 papers), AI in cancer detection (6 papers) and Lung Cancer Diagnosis and Treatment (3 papers). The work is most often cited by research in Health Informatics (14 citations), Radiology, Nuclear Medicine and Imaging (206 citations) and Neurology (41 citations). Yao‐Sian Huang has collaborated with scholars based in Taiwan, United States and Japan. Frequent co-authors include Ruey‐Feng Chang, Chiun‐Sheng Huang, Rong‐Tai Chen, Yeun‐Chung Chang, Hsin‐Ming Chen, Cher‐Wei Liang, Chia‐Hung Chen, Chih‐Yen Tu, Wei‐Ren Lan and Yan‐Wei Lee. Their work appears in journals such as IEEE Transactions on Medical Imaging, Medical Physics and Ultrasound in Medicine & Biology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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