2011 - ACM Senior Member
The scientist’s investigation covers issues in Information retrieval, Artificial intelligence, Computational biology, Data mining and Genetics. His work on Information extraction as part of his general Information retrieval study is frequently connected to Cognitive models of information retrieval, Management information systems and Personal information management, thereby bridging the divide between different branches of science. His work in Artificial intelligence addresses issues such as Natural language processing, which are connected to fields such as Test set and Named-entity recognition.
His Computational biology research is multidisciplinary, incorporating elements of Service and MEDLINE. His studies in Data mining integrate themes in fields like Web service, Web modeling, Knowledge representation and reasoning and Knowledge base. His study in the field of Biological database, Genomics and Gene also crosses realms of Genetic association.
Chun-Nan Hsu mostly deals with Artificial intelligence, Data mining, Information retrieval, Natural language processing and Genetics. His Image segmentation study, which is part of a larger body of work in Artificial intelligence, is frequently linked to Focus, bridging the gap between disciplines. His Data mining study combines topics in areas such as Ranking, Support vector machine, Robustness and Knowledge-based systems.
His Information retrieval study frequently links to adjacent areas such as Web modeling. The various areas that Chun-Nan Hsu examines in his Natural language processing study include Annotation and Named-entity recognition. His work on Gene, Interaction network, Genomics and Human genome as part of general Genetics study is frequently connected to Gene expression profiling, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
Chun-Nan Hsu spends much of his time researching Artificial intelligence, Natural language processing, Information retrieval, Data science and Deep learning. His Artificial intelligence study incorporates themes from Scalability and Reduction. His work deals with themes such as Space, Face and Embedding, which intersect with Natural language processing.
His Information retrieval research is multidisciplinary, incorporating perspectives in Supervised learning, Feature and Biomedical text mining. The Deep learning study combines topics in areas such as Metadata, Data point and Named-entity recognition. As part of the same scientific family, Chun-Nan Hsu usually focuses on Named-entity recognition, concentrating on Classifier and intersecting with Recurrent neural network.
Chun-Nan Hsu focuses on Artificial intelligence, Information retrieval, Clinical decision support system, Natural language processing and Locality-sensitive hashing. In general Artificial intelligence study, his work on Deep learning and Data point often relates to the realm of Relevant information, Proof of concept and Pediatric patient, thereby connecting several areas of interest. Chun-Nan Hsu merges Information retrieval with Metric in his study.
His Clinical decision support system research includes elements of Vocabulary, Human microbiome, Knowledge base and Reading. His Natural language processing research includes elements of Pediatric emergency medicine, Kawasaki disease, Test, Emergency department and Delayed diagnosis. Chun-Nan Hsu has researched Statistical model in several fields, including Jaccard index and Data mining.
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Generating finite-state transducers for semi-structured data extraction from the Web
Chun-Nan Hsu;Ming-Tzung Dung.
Information Systems (1998)
Retrieving and Integrating Data from Multiple Information Sources
Yigal Arens;Chin Y. Chee;Chun-Nan Hsu;Craig A. Knoblock.
International Journal of Cooperative Information Systems (1993)
FASTSNP: an always up-to-date and extendable service for SNP function analysis and prioritization
Hsiang-Yu Yuan;Jen-Jie Chiou;Wen-Hsien Tseng;Chia-Hung Liu.
Nucleic Acids Research (2006)
Overview of BioCreative II gene mention recognition
Larry Smith;Lorraine K Tanabe;Rie Johnson nee Ando;Cheng-Ju Kuo.
Overview of BioCreative II gene normalization.
Alexander A. Morgan;Zhiyong Lu;Xinglong Wang;Aaron M. Cohen.
Genome Biology (2008)
Query processing in the SIMS information mediator
Yigal Arens;Chun-Nan Hsu;Craig A. Knoblock.
Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence
Huiying Liang;Brian Y. Tsui;Hao Ni;Carolina C. S. Valentim.
Nature Medicine (2019)
Weakly supervised learning of biomedical information extraction from curated data
Suvir Jain;R Kashyap;Tsung-Ting Kuo;Shitij Bhargava.
BMC Bioinformatics (2016)
Automatic information extraction from semi-structured Web pages by pattern discovery
Chia-Hui Chang;Chun-Nan Hsu;Shao-Cheng Lui.
decision support systems (2003)
The gene normalization task in BioCreative III
Zhiyong Lu;Hung-Yu Kao;Chih-Hsuan Wei;Minlie Huang.
BMC Bioinformatics (2011)
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