diem le thi - Academia.edu (original) (raw)

Papers by diem le thi

Drug Metabolism and Pharmacokinetics, 2008

The pharmacokinetics of dihydroartemisinin (DHA) in a 5-day oral monotherapy regimen was investig... more The pharmacokinetics of dihydroartemisinin (DHA) in a 5-day oral monotherapy regimen was investigated in ten adult Vietnamese patients with uncomplicated falciparum malaria. The patients were treated with a total dose of 900 mg DHA divided as single daily doses of 300, 300, 100, 100, and 100 mg from day 0 through day 4. There were no differences in the concentrations of DHA within the first two days of treatment. The pharmacokinetics of DHA in the acute phase, however, was significantly different from that in the convalescent phase of malaria. Reduced half-life (T(1/2z)) and lower area under concentration curve (AUC(infinity)) values were observed on the final day of treatment in comparison to those obtained on the first day. These decreases in T(1/2z) and AUC(infinity) were observed in concordance with increased drug clearance (CL/F). Furthermore, the time required to reach maximum plasma DHA concentration (T(max)) on day 4 was shorter than that on day 0. Together, these findings suggest that the change in pharmacokinetics of DHA is related to the physiological change in malaria patients between the acute and convalescent phases of the disease.

Journal of Travel & Tourism Marketing, 2011

Paradoxically, part of the appeal of Vietnam as an emerging destination lies in the commodificati... more Paradoxically, part of the appeal of Vietnam as an emerging destination lies in the commodification of images, artifacts, and battlefield sites of the Vietnam War. While studied from the supply-side, little research has been undertaken yet in terms of the patterns of demand for battlefield tourism. Based on a survey of 481 visitors to the former Demilitarized Zone (DMZ), this article uses factor analysis and cluster analysis to segment then profile battlefield visitors based on their motivations. Three groups of visitors to the DMZ were identified: the Battlefield Tourism Enthusiast, the Opportunist, and Passive Tourists. Significant differences were found between the three segments with regard to various sociodemographics and trip characteristics. However, results from the study also emphasize that analyses of demand based on site visits should be contextualized in terms of visits to the country as a whole and that care must be taken in distinguishing specialist visitors from generalists.

In this paper, we present a knowledge-assisted approach to index and retrieve large volume of med... more In this paper, we present a knowledge-assisted approach to index and retrieve large volume of medical images. Both images and associated texts are indexed using medical concepts from the Unified Medical Language System (UMLS) metathesaurus. We propose a structured learning framework for modular acquisition of medical semantics from images with complementary global and local image indexing schemes. Two fusion approaches are also developed to improve text retrieval using the UMLS-based image indexing: a simple post-query fusion and a visual modality filtering to remove visually aberrant images according to the query modality concepts. On the ImageCLEFmed 2005 database, our framework outperformed our previous result which ranked top in the ImageCLEFmed 2005 Medical Image Retrieval task benchmark.

We describe a conceptual indexing method using UMLS meta-thesaurus. Concepts are automatically ma... more We describe a conceptual indexing method using UMLS meta-thesaurus. Concepts are automatically mapped from text using MetaMap software tool for English, and a simplified mapping tool for other languages. The concepts and their semantic links given by UMLS are used to build a Bayesien network. Retrieval process is then an inference process of probabilities or weights. Different types of relations are experimented in this model to evaluate their efficiency in retrieval.

IEEE Transactions on Circuits and Systems for Video Technology, 2007

Voluminous medical images are generated daily. They are critical assets for medical diagnosis, re... more Voluminous medical images are generated daily. They are critical assets for medical diagnosis, research, and teaching. To facilitate automatic indexing and retrieval of large medical-image databases, both images and associated texts are indexed using medical concepts from the Unified Medical Language System (UMLS) meta-thesaurus. We propose a structured learning framework based on support vector machines to facilitate modular design and learning of medical semantics from images. We present two complementary visual indexing approaches within this framework: a global indexing to access image modality and a local indexing to access semantic local features. Two fusion approaches are developed to improve textual retrieval using the UMLS-based image indexing. First, a simple fusion of the textual and visual retrieval approaches is proposed, improving significantly the retrieval results of both text and image retrieval. Second, a visual modality filtering is designed to remove visually aberrant images according to the query modality concept(s). Using the ImageCLEFmed database, we demonstrate the effectiveness of our framework which is superior when compared with the automatic runs evaluated in 2005 on the same medical-image retrieval task.

Conceptual Indexing is a way to produce only one index for many multilingual documents. Inter-Med... more Conceptual Indexing is a way to produce only one index for many multilingual documents. Inter-Media conceptual indexing promotes the use of common concepts between two media in order to use a single index for several media. In this paper we explore such an advance indexing point of view. We show the benefit of an automatic conceptual indexing for texts and its extension for text and image documents. Tests are conducted on the multilingual image and text medical document corpus of the CLEF initiative, where we obtain best results on text in 2005 and 2006, and show promising results on images, and best results for the combination of image and text.

To facilitate the automatic indexing and retrieval of large medical image databases, images and a... more To facilitate the automatic indexing and retrieval of large medical image databases, images and associated texts are indexed using concepts from the Unified Medical Language System (UMLS) meta-thesaurus. We propose a structured learning framework for learning medical semantics from images. Two complementary global and local visual indexing approaches are presented. Two fusion approaches are also used to improve textual retrieval using the UMLS-based image indexing: a simple post-query fusion and a visual modality filtering to remove visually aberrant images according to the query modality concepts. Using the ImageCLEFmed database, we demonstrate that our framework is superior when compared to the automatic runs evaluated in 2005 on the same Medical Image Retrieval task.

UMLS is known as largest thesaurus in biomedical domain constructed by Library National of Medici... more UMLS is known as largest thesaurus in biomedical domain constructed by Library National of Medicine. In this paper, we aim to evaluate effect of the exploration of UMLS knowledge in medical domain information retrieval by mapping large text of collection ImageCLEFMed to UMLS concepts, and expanding queries and documents automatically base on semantic relations in the UMLS hierarchy. We get the encouraging result with the best enhancement on MAP of 66% compared to text only retrieval, and 34% compared to conceptual indexing baseline.

We promote the use of explicit medical knowledge to solve retrieval of information both visual an... more We promote the use of explicit medical knowledge to solve retrieval of information both visual and textual. For text, this knowledge is a set of concepts from a Meta-thesaurus, the Unified Medical Language System (UMLS). For images, this knowledge is a set of semantic features that are learned from examples using SVM within a structured learning framework. Image and text index are represented in the same way: a vector of concepts. The use of concepts allows the expression of a common index form: an inter-media index, offering the opportunity of homogeneous indexing/querying time fusion techniques. Top results obtained with concept based approaches show the potential of conceptual indexing.

Drug Metabolism and Pharmacokinetics, 2008

The pharmacokinetics of dihydroartemisinin (DHA) in a 5-day oral monotherapy regimen was investig... more The pharmacokinetics of dihydroartemisinin (DHA) in a 5-day oral monotherapy regimen was investigated in ten adult Vietnamese patients with uncomplicated falciparum malaria. The patients were treated with a total dose of 900 mg DHA divided as single daily doses of 300, 300, 100, 100, and 100 mg from day 0 through day 4. There were no differences in the concentrations of DHA within the first two days of treatment. The pharmacokinetics of DHA in the acute phase, however, was significantly different from that in the convalescent phase of malaria. Reduced half-life (T(1/2z)) and lower area under concentration curve (AUC(infinity)) values were observed on the final day of treatment in comparison to those obtained on the first day. These decreases in T(1/2z) and AUC(infinity) were observed in concordance with increased drug clearance (CL/F). Furthermore, the time required to reach maximum plasma DHA concentration (T(max)) on day 4 was shorter than that on day 0. Together, these findings suggest that the change in pharmacokinetics of DHA is related to the physiological change in malaria patients between the acute and convalescent phases of the disease.

Journal of Travel & Tourism Marketing, 2011

Paradoxically, part of the appeal of Vietnam as an emerging destination lies in the commodificati... more Paradoxically, part of the appeal of Vietnam as an emerging destination lies in the commodification of images, artifacts, and battlefield sites of the Vietnam War. While studied from the supply-side, little research has been undertaken yet in terms of the patterns of demand for battlefield tourism. Based on a survey of 481 visitors to the former Demilitarized Zone (DMZ), this article uses factor analysis and cluster analysis to segment then profile battlefield visitors based on their motivations. Three groups of visitors to the DMZ were identified: the Battlefield Tourism Enthusiast, the Opportunist, and Passive Tourists. Significant differences were found between the three segments with regard to various sociodemographics and trip characteristics. However, results from the study also emphasize that analyses of demand based on site visits should be contextualized in terms of visits to the country as a whole and that care must be taken in distinguishing specialist visitors from generalists.

In this paper, we present a knowledge-assisted approach to index and retrieve large volume of med... more In this paper, we present a knowledge-assisted approach to index and retrieve large volume of medical images. Both images and associated texts are indexed using medical concepts from the Unified Medical Language System (UMLS) metathesaurus. We propose a structured learning framework for modular acquisition of medical semantics from images with complementary global and local image indexing schemes. Two fusion approaches are also developed to improve text retrieval using the UMLS-based image indexing: a simple post-query fusion and a visual modality filtering to remove visually aberrant images according to the query modality concepts. On the ImageCLEFmed 2005 database, our framework outperformed our previous result which ranked top in the ImageCLEFmed 2005 Medical Image Retrieval task benchmark.

We describe a conceptual indexing method using UMLS meta-thesaurus. Concepts are automatically ma... more We describe a conceptual indexing method using UMLS meta-thesaurus. Concepts are automatically mapped from text using MetaMap software tool for English, and a simplified mapping tool for other languages. The concepts and their semantic links given by UMLS are used to build a Bayesien network. Retrieval process is then an inference process of probabilities or weights. Different types of relations are experimented in this model to evaluate their efficiency in retrieval.

IEEE Transactions on Circuits and Systems for Video Technology, 2007

Voluminous medical images are generated daily. They are critical assets for medical diagnosis, re... more Voluminous medical images are generated daily. They are critical assets for medical diagnosis, research, and teaching. To facilitate automatic indexing and retrieval of large medical-image databases, both images and associated texts are indexed using medical concepts from the Unified Medical Language System (UMLS) meta-thesaurus. We propose a structured learning framework based on support vector machines to facilitate modular design and learning of medical semantics from images. We present two complementary visual indexing approaches within this framework: a global indexing to access image modality and a local indexing to access semantic local features. Two fusion approaches are developed to improve textual retrieval using the UMLS-based image indexing. First, a simple fusion of the textual and visual retrieval approaches is proposed, improving significantly the retrieval results of both text and image retrieval. Second, a visual modality filtering is designed to remove visually aberrant images according to the query modality concept(s). Using the ImageCLEFmed database, we demonstrate the effectiveness of our framework which is superior when compared with the automatic runs evaluated in 2005 on the same medical-image retrieval task.

Conceptual Indexing is a way to produce only one index for many multilingual documents. Inter-Med... more Conceptual Indexing is a way to produce only one index for many multilingual documents. Inter-Media conceptual indexing promotes the use of common concepts between two media in order to use a single index for several media. In this paper we explore such an advance indexing point of view. We show the benefit of an automatic conceptual indexing for texts and its extension for text and image documents. Tests are conducted on the multilingual image and text medical document corpus of the CLEF initiative, where we obtain best results on text in 2005 and 2006, and show promising results on images, and best results for the combination of image and text.

To facilitate the automatic indexing and retrieval of large medical image databases, images and a... more To facilitate the automatic indexing and retrieval of large medical image databases, images and associated texts are indexed using concepts from the Unified Medical Language System (UMLS) meta-thesaurus. We propose a structured learning framework for learning medical semantics from images. Two complementary global and local visual indexing approaches are presented. Two fusion approaches are also used to improve textual retrieval using the UMLS-based image indexing: a simple post-query fusion and a visual modality filtering to remove visually aberrant images according to the query modality concepts. Using the ImageCLEFmed database, we demonstrate that our framework is superior when compared to the automatic runs evaluated in 2005 on the same Medical Image Retrieval task.

UMLS is known as largest thesaurus in biomedical domain constructed by Library National of Medici... more UMLS is known as largest thesaurus in biomedical domain constructed by Library National of Medicine. In this paper, we aim to evaluate effect of the exploration of UMLS knowledge in medical domain information retrieval by mapping large text of collection ImageCLEFMed to UMLS concepts, and expanding queries and documents automatically base on semantic relations in the UMLS hierarchy. We get the encouraging result with the best enhancement on MAP of 66% compared to text only retrieval, and 34% compared to conceptual indexing baseline.

We promote the use of explicit medical knowledge to solve retrieval of information both visual an... more We promote the use of explicit medical knowledge to solve retrieval of information both visual and textual. For text, this knowledge is a set of concepts from a Meta-thesaurus, the Unified Medical Language System (UMLS). For images, this knowledge is a set of semantic features that are learned from examples using SVM within a structured learning framework. Image and text index are represented in the same way: a vector of concepts. The use of concepts allows the expression of a common index form: an inter-media index, offering the opportunity of homogeneous indexing/querying time fusion techniques. Top results obtained with concept based approaches show the potential of conceptual indexing.