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In modern medical systems huge amount of text, words, images and videos are produced and stored in ad hoc databases. Medical community needs to extract precise information from that large amount of data. Currently ICT approaches do not provide a methodology for content-based medical images retrieval and classification. On the other hand, from the Internet of Things (IoT) perspective, the ICT medical data can be produced by several devices. Produced data complies with all Big Data features and constraints. The IoT guidelines put at the center of the system a new smart software to manage and transform Big Data in a new understanding form. This paper describes a text based indexing system for mammographic images retrieval and classification. The system deals with text (structured reports) and images (mammograms) mining and classification in a typical Department of Radiology. DICOM structured reports, containing free text for medical diagnosis, have been analyzed and labeled in order to classify the corresponding mammographic images. Information Retrieval process is based on some text manipulation techniques, such as light semantic analysis, stop-word removing, and light medical natural language processing. The system includes also a Search Engine module, based on a Bayes Naive Classifier. The experimental results provide interesting performance in terms of Specificity and Sensibility. Two more indexes have been computed in order to assess the system robustness: the A z (Area under ROC Curve) index and the σ A z ( A z standard error) index. The dataset is composed of healthy and pathological DICOM structured reports. Two use case scenarios are presented and described to prove the effectiveness of the proposed approach.

The CALMA (Computer Assisted Library for MAmmography) project is a five years plan developed in a physics research frame in collaboration between INFN (Istituto Nazionale di Fisica Nucleare) and many Italian hospitals. At present a large database of digitized mammographic images (more than 6000) was collected and a software based on neural network algorithms for the search of suspicious breast lesions was developed. Two tools are available: a microcalcification clusters hunter, based on supervised and unsupervised feedforward neural network, and a massive lesions searcher, based on a hibrid approach. Both the algorithms analyzed preprocessed digitized images by high frequency filters. Clinical tests were performed to evaluate sensitivity and specificity of the system, considering the system as alone and as secon reader. Results show that the system is ready to be implemented by medical industry. The CALMA project, just ended, has its natural development in the GPCALMA (Grid Platform for CALMA) project, where distributed users join common resources (images, tools, statistical analysis)., Comment: 3 pages, 1 figure; to appear in the Proceedings of Frontier Detectors For Frontier Physics, 9th Pisa Meeting on Advanced Detectors, 25-31 May 2003, La Biodola, Isola d'Elba, Italy

The ectoparasitoid Bracon hebetor Say is an insect frequently found in storage facilities, where it attacks stored grain pests. The biology of this parasitoid was studied when reared on seven different artificial diets (in vitro rearing), under controlled temperature (25 ± 2 °C), relative humidity (60 ± 10%), and photoperiod (14-h photophase), and compared to its biology on its natural host Anagasta kuehniella (Zeller) (in vivo rearing). The artificial diet contained 60% holotissue of Diatraea saccharalis (Fabricius) pupae, 12% fetal bovine serum, 12% lactoalbumin hydrolysate, and 16% egg yolk, enabled development similar to that obtained on the natural host. The life cycle duration (egg–adult) was not significantly different, and the adults reared on this diet promptly paralyzed and parasitized the natural host, though at a lower proportion than those reared in vivo. There was no difference in the longevity of females obtained with these two different rearing systems (in vivo and in vitro). However, about 60% of the larvae developed on the diet failed to produce a protective cocoon during the pupal phase, indicating a sub-optimal quality associated with this artificial medium.

The objective of this study was to determine the prevalence of asthma-related symptoms in the Guadalajara Health Area, using the methods prescribed by the first phase of the European Asthma Study (EAS). A transversal descriptive study by self-administered questionnaire in a population of 2,968 subjects aged 20 to 44 years old assigned to the Guadalajara Health Area was performed. The study took place between September 1995 and February 1996. We received 2,435 responses (81.2% of the sample). Each symptom was studied in relation to sex, age, domicile and smoking and the results were compared to data from other Spanish health areas participating in the EAS. Significant differences were found between our results and those of other Spanish health areas. Subjects reporting asthma symptoms accounted for 8.6% (C.I. 7.5% to 9.8%) of the sample. Presence of asthma was related to place of residence but not to age or sex.