Lean manufacturing: a systematic review in the food industry

Este artículo describe las tendencias de estudio de manufactura esbelta mediante una revisión sistemática de la literatura entre los años 2015 y 2019 de las principales bases de datos bibliográficas. Se recuperaron 3776 artículos y se aplicó un análisis de conglomerado bibliométrico por tema y año con los metadatos y la herramienta VOSviewer. Los resultados indican que la base de datos con mayor número de publicaciones es Science Reseach. El 36% del total de los artículos recuperados son de países de oriente, los cuales abordan la eficiencia de procesos productivos y la productividad. Se proporciona un análisis de la implementación de la filosofía de manufactura esbelta, así como un resumen de las herramientas utilizadas en empresas del sector de alimentos. Finalmente, se propone un marco general que resume las tendencias en la temática de manufactura esbelta a partir de la revisión de literatura desarrollada en el presente trabajo.This paper describes the study trends of lean manufacturing at a national and international level through a systematic review of the scientific literature between 2015 and 2019. A total of 3776 research articles were retrieved from the main bibliographic databases. Metadata and VOSviewer were used to perform a bibliometric cluster analysis by topic and year. The results indicated that the database with the largest number of publications was Science Research. In addition, 36% of all the research articles retrieved were from Asian countries and they addressed efficiency of production processes and productivity. The present article provided an analysis of the implementation of the lean manufacturing philosophy and a summary of the tools used in companies in the food sector to generate inputs that promote productivity. A general framework is proposed that summarizes the trends in lean manufacturing from the literature review performed here

Front Pharmacol

Pharmacovigilance consists in monitoring and preventing the occurrence of adverse drug reactions. This activity can be time-consuming because it requires the collection of both patient and medication information. In this paper, we present two visualization and data mining applications to make this task easier for the practitioner. These tools have been developed and tested using the biomedical data warehouse eHOP (Hospital Biomedical Data Warehouse) of the Rennes University Hospital Centre. The first application is a tool to visualize the patient electronic health record in the form of a timeline. All patient data is collected and displayed chronologically. The usability test of the timeline has been very positive (SUS score: 82.5) and the tool is now available for practitioners in their daily practice. The second application is a tool to visualize and search the sequences of a patient cohort. The visual interface allow user to quickly visualize sequences. A query builder allows user to search for sequences in relation with a reference sequence, such as a prescription sequence followed by an abnormal biological value. The sequences are then visually aligned with this reference sequence and ranked by similarity. The GSP (Generalized Sequential Pattern) and Apriori algorithms allow us to display a summary of the sequences list by searching for common sequences and associations. The tool was tested on a use case which consisted in detection of inappropriate drug administration. Compared to a random order, we showed this ranking system saved the practitioner time in this task (to analyze one sequence, 3.49 +/- 3.54 vs. 2.26 +/- 2.86 s, p = 0.0003). These two visualization and data mining applications will help the daily practice of pharmacovigilance

Cancer risks associated with germline PALB2 pathogenic variants: An international study of 524 families

PURPOSE To estimate age-specific relative and absolute cancer risks of breast cancer and to estimate risks of ovarian, pancreatic, male breast, prostate, and colorectal cancers associated with germline PALB2 pathogenic variants (PVs) because these risks have not been extensively characterized. METHODS We analyzed data from 524 families with PALB2 PVs from 21 countries. Complex segregation analysis was used to estimate relative risks (RRs; relative to country-specific population incidences) and absolute risks of cancers. The models allowed for residual familial aggregation of breast and ovarian cancer and were adjusted for the family-specific ascertainment schemes. RESULTS We found associations between PALB2 PVs and risk of female breast cancer (RR, 7.18; 95% CI, 5.82 to 8.85; P = 6.5 × 10-76), ovarian cancer (RR, 2.91; 95% CI, 1.40 to 6.04; P = 4.1 × 10-3), pancreatic cancer (RR, 2.37; 95% CI, 1.24 to 4.50; P = 8.7 × 10-3), and male breast cancer (RR, 7.34; 95% CI, 1.28 to 42.18; P = 2.6 3 1022). There was no evidence for increased risks of prostate or colorectal cancer. The breast cancer RRs declined with age (P for trend = 2.0 × 10-3). After adjusting for family ascertainment, breast cancer risk estimates on the basis of multiple case families were similar to the estimates from families ascertained through population-based studies (P for difference = .41). On the basis of the combined data, the estimated risks to age 80 years were 53% (95% CI, 44% to 63%) for female breast cancer, 5% (95% CI, 2% to 10%) for ovarian cancer, 2%-3% (95% CI females, 1% to 4%; 95% CI males, 2% to 5%) for pancreatic cancer, and 1% (95% CI, 0.2% to 5%) for male breast cancer. CONCLUSION These results confirm PALB2 as a major breast cancer susceptibility gene and establish substantial associations between germline PALB2 PVs and ovarian, pancreatic, and male breast cancers. These findings will facilitate incorporation of PALB2 into risk prediction models and optimize the clinical cancer risk management of PALB2 PV carriers

Evaluating predictive modeling algorithms to assess patient eligibility for clinical trials from routine data

Background The necessity to translate eligibility criteria from free text into decision rules that are compatible with data from the electronic health record (EHR) constitutes the main challenge when developing and deploying clinical trial recruitment support systems. Recruitment decisions based on case-based reasoning, i.e. using past cases rather than explicit rules, could dispense with the need for translating eligibility criteria and could also be implemented largely independently from the terminology of the EHR’s database. We evaluated the feasibility of predictive modeling to assess the eligibility of patients for clinical trials and report on a prototype’s performance for different system configurations. Methods The prototype worked by using existing basic patient data of manually assessed eligible and ineligible patients to induce prediction models. Performance was measured retrospectively for three clinical trials by plotting receiver operating characteristic curves and comparing the area under the curve (ROC-AUC) for different prediction algorithms, different sizes of the learning set and different numbers and aggregation levels of the patient attributes. Results Random forests were generally among the best performing models with a maximum ROC-AUC of 0.81 (CI: 0.72-0.88) for trial A, 0.96 (CI: 0.95-0.97) for trial B and 0.99 (CI: 0.98-0.99) for trial C. The full potential of this algorithm was reached after learning from approximately 200 manually screened patients (eligible and ineligible). Neither block- nor category-level aggregation of diagnosis and procedure codes influenced the algorithms’ performance substantially. Conclusions Our results indicate that predictive modeling is a feasible approach to support patient recruitment into clinical trials. Its major advantages over the commonly applied rule-based systems are its independency from the concrete representation of eligibility criteria and EHR data and its potential for automation

MODÉLISATION D'ANTENNES TRÈS BASSES FRÉQUENCES (VLF/LF) : étude de l'influence de la structure, des composants associés et de l'environnement en vue de leur optimisation

Communications with Low Frequencies (LF) and Very low frequencies (VLF) are used for military purposes, specially for communicating worldwide with submarines underwater at shallow depths. The modeling and simulation of such antennas require numerical methods close to their validity limits. The subject of this thesis deals with the global modelization of VLF/LF [3-300 kHz] antenna structure taking into account the local environment such as : insulators, ground plane, buildings,... The first part of the thesis is devoted to the characterization of insulators. The behavior of these devices subjected to high voltages being unknown in the VLF/LF. A second part is devoted to the developpment of a “Thin Wire” model arbitrarily oriented integrating localized components. Three methods are presented and validated by comparison with theorical results. Finally, simulations of VLF antennas taking into account the numerous radiating arbitrarily oriented wires with surrounding insulators are presented.Les télécommunications très basses fréquences (Very Low Frequency/Low Frequency) sont utilisées pour les communications militaires à couverture mondiale avec des sous-marins en plongée. La simulation de ces antennes nécessite l'utilisation de méthodes numériques bien souvent en limite de leur domaine de validité. L'objectif de la thèse est de développer un outil de modélisation globale des structures antennaires VLF/LF [3-300 kHz] prenant en compte l'environnement proche tels que les isolateurs, les structures de soutien, le plan de sol, les bâtiments annexes, ... Une première partie est consacrée à la caractérisation des isolateurs. Le comportement de ces dispositifs soumis à de très hautes tensions est en effet peu connu dans la bande de fréquences VLF/LF. Une seconde partie est consacrée à l'élaboration et au développement d'un modèle de "Fil Mince" arbitrairement orienté intégrant des composants localisés. Trois méthodes sont présentées puis validées par comparaison à des résultats théoriques. Enfin l'étude de l'influence de la structure de soutien sur le fonctionnement des antennes VLF/LF est présentée

The French Health Data Hub and the German Medical Informatics Initiatives Two National Projects to Promote Data Sharing in Healthcare

International audienc