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17 results on '"Alva, Alicia"'

10. Automatic classification of pediatric pneumonia based on lung ultrasound pattern recognition

Author

Correa, Malena, primary, Zimic, Mirko, additional, Barrientos, Franklin, additional, Barrientos, Ronald, additional, Román-Gonzalez, Avid, additional, Pajuelo, Mónica J., additional, Anticona, Cynthia, additional, Mayta, Holger, additional, Alva, Alicia, additional, Solis-Vasquez, Leonardo, additional, Figueroa, Dante Anibal, additional, Chavez, Miguel A., additional, Lavarello, Roberto, additional, Castañeda, Benjamín, additional, Paz-Soldán, Valerie A., additional, Checkley, William, additional, Gilman, Robert H., additional, and Oberhelman, Richard, additional

Published
2018
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12. [Implementation of a telediagnostic system for tuberculosis and determination of multi-drug resistance based in the MODS method in Trujillo, Peru]

Author

Rodríguez, Luis, Alva, Alicia, Coronel, Jorge, Caviedes, Luz, Mendoza-Ticona, Alberto, Gilman, Robert, Sheen, Patricia, and Zimic, Mirko

Subjects
Diagnostic Imaging, insuficiencia multiorgánica, lcsh:R5-920, Bacteriological Techniques, lcsh:R, lcsh:Medicine, Microbial Sensitivity Tests, Mycobacterium tuberculosis, tuberculosis resistente a múltiples medicamentos, Multiple organ failure, Tuberculosis, multidrug-resistant, Telemedicine, Peru, Tuberculosis, Multidrug-Resistant, Humans, Tuberculosis, lcsh:Medicine (General), Insuficiencia multiorgánica, Tuberculosis resistente a múltiples medicamentos, Algorithms
Abstract

Objectives. To implement a system for remote diagnosis of tuberculosis and multidrug resistance (MDR) using the Microscopic-Observation Drug Susceptibility Assay (MODS) method in the Mycobacteria Laboratory, Trujillo Center of Excellence in Tuberculosis (CENEX-Trujillo). The system included a variant of an algorithm for recognition of Mycobacterium tuberculosis recently reported from digital images of MODS cultures of sputum samples. Materials and methods. The recognition algorithm was optimized using a retraining statistical model based on digital images of MODS cultures from CENEX-Trujillo. Images of 50 positive MODS cultures of patients with suspected multidrug-resistant tuberculosis were obtained between January and October 2012 in the CENEX-Trujillo. Results. The sensitivity and specificity to recognize strings of tuberculosis were 92.04% and 94.93% respectively using objects. The sensitivity and specificity to determine a positive tuberculosis field were 95.4% and 98.07% respectively using pictures. Conclusions. The results demonstrated the feasibility of the implementation of telediagnostics in remote locations, which may contribute to the early detection of multidrug-resistant tuberculosis by MODS method. Objetivos. Implementar un sistema para el diagnóstico remoto de tuberculosis y multidrogorresistencia (MDR) usando el método Microscopic-Observation Drug Susceptibility Assay (MODS) en el Laboratorio de Micobacterias del Centro de Excelencia en Tuberculosis de Trujillo (CENEX-Trujillo). El sistema incluyó una variante de un algoritmo de reconocimiento de Mycobacterium tuberculosis recientemente reportado a partir de imágenes digitales de cultivos MODS de muestras de esputo. Materiales y métodos. Se optimizó un algoritmo de reconocimiento por medio de un reentrenamiento del modelo estadístico basado en imágenes digitales de cultivos MODS provenientes del Laboratorio de Micobacterias del CENEX-Trujillo. Se obtuvieron imágenes de 50 cultivos MODS positivos de pacientes con sospecha de tuberculosis multidrogorresistente entre enero y octubre de 2012 en el CENEX-Trujillo. Resultados. La sensibilidad y la especificidad en objetos, para reconocer cordones de tuberculosis fueron de 92,04% y de 94,93% respectivamente. La sensibilidad y la especificidad en foto, para determinar un campo positivo a tuberculoisis fueron 95,4% y de 98,07% respectivamente. Conclusiones. Los resultados demostraron la factibilidad de la implementación de telediagnóstico en lugares remotos, el cual puede contribuir con la detección temprana de tuberculosis multidrogorresistente mediante el método MODS.

Published
2014

13. Filtering of the skin portion on lung ultrasound digital images to facilitate automatic diagnostics of pneumonia

Author

Barrientos, Franklin, primary, Roman-Gonzalez, Avid, additional, Barrientos, Ronald, additional, Solis, Leonardo, additional, Alva, Alicia, additional, Correa, Malena, additional, Pajuelo, Monica, additional, Anticona, Cynthia, additional, Lavarello, Roberto, additional, Castaneda, Benjamin, additional, Oberhelman, Richard, additional, Gilman, Robert H., additional, and Zimic, Mirko, additional

Published
2016
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14. Etiological Role and Repeated Infections of Sapovirus among Children Aged Less than 2 Years in a Cohort Study in a Peri-urban Community of Peru

Author

Liu, Xiaofang, primary, Jahuira, Helena, additional, Gilman, Robert H., additional, Alva, Alicia, additional, Cabrera, Lilia, additional, Okamoto, Michiko, additional, Xu, Hang, additional, Windle, Henry J., additional, Kelleher, Dermot, additional, Varela, Marco, additional, Verastegui, Manuela, additional, Calderon, Maritza, additional, Sanchez, Gerardo, additional, Sarabia, Vanessa, additional, Ballard, Sarah B., additional, Bern, Caryn, additional, Mayta, Holger, additional, Crabtree, Jean E., additional, Cama, Vitaliano, additional, Saito, Mayuko, additional, and Oshitani, Hitoshi, additional

Published
2016
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16. Morphological Characterization of Mycobacterium tuberculosis in a MODS Culture for an Automatic Diagnostics through Pattern Recognition

Author

Alva, Alicia, primary, Aquino, Fredy, additional, Gilman, Robert H., additional, Olivares, Carlos, additional, Requena, David, additional, Gutiérrez, Andrés H., additional, Caviedes, Luz, additional, Coronel, Jorge, additional, Larson, Sandra, additional, Sheen, Patricia, additional, Moore, David A. J., additional, and Zimic, Mirko, additional

Published
2013
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17. Morphological Characterization of Mycobacterium tuberculosis in a MODS Culture for an Automatic Diagnostics through Pattern Recognition.

Author

Alva, Alicia, Aquino, Fredy, Gilman, Robert H., Olivares, Carlos, Requena, David, Gutiérrez, Andrés H., Caviedes, Luz, Coronel, Jorge, Larson, Sandra, Sheen, Patricia, Moore, David A. J., and Zimic, Mirko

Subjects
*MYCOBACTERIUM tuberculosis, *PATTERN recognition systems, *ROUTINE diagnostic tests, *DIGITAL images, *SPUTUM, *DIAGNOSIS, *THERAPEUTICS
Abstract

Tuberculosis control efforts are hampered by a mismatch in diagnostic technology: modern optimal diagnostic tests are least available in poor areas where they are needed most. Lack of adequate early diagnostics and MDR detection is a critical problem in control efforts. The Microscopic Observation Drug Susceptibility (MODS) assay uses visual recognition of cording patterns from Mycobacterium tuberculosis (MTB) to diagnose tuberculosis infection and drug susceptibility directly from a sputum sample in 7–10 days with a low cost. An important limitation that laboratories in the developing world face in MODS implementation is the presence of permanent technical staff with expertise in reading MODS. We developed a pattern recognition algorithm to automatically interpret MODS results from digital images. The algorithm using image processing, feature extraction and pattern recognition determined geometrical and illumination features used in an object-model and a photo-model to classify TB-positive images. 765 MODS digital photos were processed. The single-object model identified MTB (96.9% sensitivity and 96.3% specificity) and was able to discriminate non-tuberculous mycobacteria with a high specificity (97.1% M. avium, 99.1% M. chelonae, and 93.8% M. kansasii). The photo model identified TB-positive samples with 99.1% sensitivity and 99.7% specificity. This algorithm is a valuable tool that will enable automatic remote diagnosis using Internet or cellphone telephony. The use of this algorithm and its further implementation in a telediagnostics platform will contribute to both faster TB detection and MDR TB determination leading to an earlier initiation of appropriate treatment. [ABSTRACT FROM AUTHOR]

Published
2013
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