Machine learning empowering laboratory medicine / 中华检验医学杂志

Traditional data storage strategy has not capacity to meet analytical needs of medical big data possessing with mixed structure and high-dimensional features. Machine learning based on algorithms that generate models in the data is becoming an innovative source of intelligent data analysis technology in computer simulation of human learning. This paper gives an introduction to the development of machine learning and its current background of medical big data. Emphases are placed on applications of machine learning in the medical image recognition, automated validation for test reports, Chinese medical language processing and computer-aided diagnosis. The opportunities and challenges to the development of laboratory medicine which taken from machine learning worth focusing.(Chin J Lab Med, 2018, 41: 627-630)

Aplicación de los árboles de decisión en la identificación de patrones de lesiones fatales por causa externa en el municipio de Pasto, Colombia / Application of decision trees in the identification of patterns of fatal injuries by external cause in the municipality of Pasto, Colombia

Resumen Introducción: La Organización Panamericana de la Salud (OPS) desde el año 1993 y la Organización Mundial de la Salud (OMS) en 1996, aceptaron que la violencia es un problema de salud pública, situación que se corrobora en el Informe de Violencia y Salud, en el cual América Latina presentó una tasa de homicidios de 18 por cada 100.000 personas, y es considerada como una de las regiones más violentas del mundo. Objetivo: Detectar patrones delictivos con técnicas de minería de datos en el Observatorio del Delito del municipio de Pasto (Colombia). Materiales y métodos: Se aplicó Cross Industry Standard Process for Data Mining (CRISP-DM), una de las metodologías utilizadas en el desarrollo de proyectos de minería de datos en los ambientes académico e industrial. La fuente de información fue el Observatorio del Delito del municipio de Pasto, donde está almacenadas las cifras históricas, limpias y transformadas sobre las lesiones de causa externa (fatales y no fatales), registrados en 11 años. Resultados: Se construyó un modelo de clasificación basado en árboles de decisión que permitió descubrir patrones de muertes por causa externa. Para el caso de homicidios, estos sucedieron en su mayoría en la Comuna 5 de Pasto, los fines de semana, en la madrugada, en el segundo semestre del año, en la vía pública y las víctimas fueron hombres adultos, de oficios varios, la causa de los homicidios fueron riñas y se produjeron con arma de fuego. Conclusión: El conocimiento generado ayudará a los organismos gubernamentales y de seguridad a tomar decisiones eficaces en lo relacionado a la implementación de planes de prevención de delitos y seguridad ciudadana.

Abstract Introduction: The Pan American Health Organization (PHO) and the World Health Organization (WHO) accepted, since the year 1993 and 1996 respectively, that violence is a public health problem, a situation that is corroborated in the report on violence and health, in which Latin America presented a homicide rate of 18 per 100,000 people, and it is considered one of the most violent regions in the world. Objective: To detect criminal patterns with data mining techniques in the Crime Observatory of the municipality of Pasto (Colombia). Materials and methods: Cross Industry Standard Process for Data Mining (CRISP-DM) was applied, which is one of the methodologies used in the development of data mining projects in academic and industrial environments. The source of information was the Crime Observatory of the municipality of Pasto, where the historical clean and transformed figures on the injuries of external cause (fatal and nonfatal) recorded in 11 years are stored. Results: A decision tree-based classification model was built that allowed the discovery of patterns of deaths from external causes. In the case of homicide, these happened mostly in the commune 5 in Pasto under the following circumstances: during the weekends, in the early morning, in the second semester of the year and in the public thoroughfare; besides, the victims were adult men of various professions; and the cause of the homicides were quarrels and they were produced with a fire gun. Conclusion: The generated knowledge will help government and security agencies make effective decisions regarding the implementation of crime prevention and citizen security plans.

Maturation Disparity between Hand-Wrist Bones in a Chinese Sample of Normal Children: An Analysis Based on Automatic BoneXpert and Manual Greulich and Pyle Atlas Assessment

OBJECTIVE: To assess the maturation disparity of hand-wrist bones using the BoneXpert system and Greulich and Pyle (GP) atlas in a sample of normal children from China. MATERIALS AND METHODS: Our study included 229 boys and 168 girls aged 2-14 years. The bones in the hand and wrist were divided into five groups: distal radius and ulna, metacarpals, proximal phalanges, middle phalanges and distal phalanges. Bone age (BA) was assessed separately using the automatic BoneXpert and GP atlas by two raters. Differences in the BA between the most advanced and retarded individual bones and bone groups were analyzed. RESULTS: In 75.8% of children assessed with the BoneXpert and 59.4% of children assessed with the GP atlas, the BA difference between the most advanced and most retarded individual bones exceeded 2.0 years. The BA mean differences between the most advanced and most retarded individual bones were 2.58 and 2.25 years for the BoneXpert and GP atlas methods, respectively. Furthermore, for both methods, the middle phalanges were the most advanced group. The most retarded group was metacarpals for BoneXpert, while metacarpals and the distal radius and ulna were the most retarded groups according to the GP atlas. Overall, the BAs of the proximal and distal phalanges were closer to the chronological ages than those of the other bone groups. CONCLUSION: Obvious and regular maturation disparities are common in normal children. Overall, the BAs of the proximal and distal phalanges are more useful for BA estimation than those of the other bone groups.

Técnica de mineração de dados: uma revisão da literatura / Técnica de mineración de datos: una revisión de la literatura / Data mining: a literature review

Este artigo teve como objetivo realizar uma revisão da literatura sobre a técnica de mineração de dados (Data Mining - DM) nas bases de dados abrangendo o Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS), Scientific Eletronic Library Online (SCIELO) e alguns livros sobre o tema. Buscou-se uma coleta ampla utilizando as palavras data mining e mineração de dados, abrangendo o período de 1999 a 2008. Como critérios de exclusão foram utilizados os descritores: indústria mineira, minas, mineralogia; foram excluídos artigos que não esclareciam o método e as tarefas relacionadas à mineração de dados. Dos 123 artigos encontrados, 32 foram selecionados. Observou-se que o volume de dados armazenados é gigantesco e continua crescendo exponencialmente. Com isso o processo de Descoberta do Conhecimento em Bases de Dados e DM inclui tarefas e métodos para extração de conhecimento útil, interessante e indispensável na tomada de decisões rápidas nas mais diversas áreas de conhecimento.

The purpose of this study was to conduct a literature review on data mining (DM) technique in the LILACS and SciELO databases and specialized books. A broad data literature search using the words data mining (in English) and/or "mineração de dados" (in Portuguese) and limited to publications between 1999 and 2008, was conducted. The exclusion criteria were the keywords mining industry, mines, mineralogy, and publications that did not describe the methods and the tasks related to data mining. Of 123 publications retrieved, 38 were selected to review. Findings suggest that the existent amount of stored data is titanic and it continue to increase considerably. Thus, the process of knowledge discovery in databases and DM have developed tasks and methods for the retrieval of useful knowledge that may be of interest and necessary for just-in-time decision making in different areas of knowledge.

En este artículo se tuvo como objetivo realizar una revisión de la literatura sobre la técnica de mineración de datos (Data Mining - DM) en las bases de datos que abarcaban la Literatura Latino-Americana y del Caribe en Ciencias de la Salud (LILACS), Scientific Eletronic Library Online (SCIELO) y algunos libros sobre el tema. Se buscó una recolección amplia utilizando las palabras data mining y mineración de datos, en el período comprendido entre 1999 a 2008. Como criterios de exclusión fueron utilizados los descriptores: industria minera, minas, mineralogía; se excluyeron artículos que no aclaraban el método y las tareas relacionadas a la mineración de dados. De los 123 artículos encontrados, 32 fueron seleccionados. Se observó que el volumen de datos almacenados es gigantesco y continúa creciendo exponencialmente. Con eso el proceso de Descubrimiento del Conocimiento en Bases de Datos y DM incluye tareas y métodos para la extracción del conocimiento útil, interesante e indispensable para la toma de decisiones rápidas en las más diversas áreas del conocimiento.