What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Gene
- Machine learning
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.
His most cited work include:
- FASTSNP: an always up-to-date and extendable service for SNP function analysis and prioritization (485 citations)
- Retrieving and Integrating Data from Multiple Information Sources (405 citations)
- Generating finite-state transducers for semi-structured data extraction from the Web (401 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Artificial intelligence (45.22%)
- Data mining (21.66%)
- Information retrieval (19.11%)
What were the highlights of his more recent work (between 2014-2021)?
- Artificial intelligence (45.22%)
- Natural language processing (17.83%)
- Information retrieval (19.11%)
In recent papers he was focusing on the following fields of study:
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.
Between 2014 and 2021, his most popular works were:
- Evaluation and accurate diagnoses of pediatric diseases using artificial intelligence (151 citations)
- Weakly supervised learning of biomedical information extraction from curated data (150 citations)
- Building a Natural Language Processing Tool to Identify Patients With High Clinical Suspicion for Kawasaki Disease from Emergency Department Notes. (21 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Gene
- Machine learning
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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