0000000000651586

AUTHOR

Antonio Martino

showing 2 related works from this author

The SIC-GIRCG 2013 Consensus Conference on Gastric Cancer.

2014

Abstract The topic chosen by the Board of the Italian Society of Surgery for the 2013 annual Consensus Conference was gastric cancer. With this purpose, under the direction of 2 chairmen, 36 experts nominated by the Regional Societies of Surgery and by the Italian Research Group for Gastric Cancer (GIRCG) participated in an experts consensus exercise, preceded by a questionnaire and mainly held by telematic vote, in accordance with the rules of the Delphi method. The results of this Consensus Conference, presented to the 115th National Congress of the Italian Society of Surgery, and approved in plenary session, are reported in the present paper.

Malemedicine.medical_specialtyGastric cancer Surgery Chemotherapy Staging Endoscopy LaparoscopyStagingDelphi TechniqueMEDLINEDelphi methodchemotherapyEndosonographyDelphi Technique; Endosonography; Female; Humans; Italy; Lymph Node Excision; Male; Neoplasm Staging; Societies Medical; Stomach NeoplasmsStomach NeoplasmStomach NeoplasmsMedicalmedicineHumanslapaoscopyguidelinesgastric cancer; chemotherapy; staging endoscopy; lapaoscopySocieties MedicalNeoplasm StagingSettore MED/06 - ONCOLOGIA MEDICAtreatmentbusiness.industryConsensus conferenceCancerEndoscopymedicine.diseasePlenary sessionSurgerySettore MED/18 - Chirurgia GeneraleGastric CancerItalyLymph Node ExcisionNeoplasm stagingLaparoscopySurgeryFemaleguidelines; Gastric Cancer; treatmentbusinessSocietiesstaging endoscopyHuman
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Predicting lorawan behavior. How machine learning can help

2020

Large scale deployments of Internet of Things (IoT) networks are becoming reality. From a technology perspective, a lot of information related to device parameters, channel states, network and application data are stored in databases and can be used for an extensive analysis to improve the functionality of IoT systems in terms of network performance and user services. LoRaWAN (Long Range Wide Area Network) is one of the emerging IoT technologies, with a simple protocol based on LoRa modulation. In this work, we discuss how machine learning approaches can be used to improve network performance (and if and how they can help). To this aim, we describe a methodology to process LoRaWAN packets a…

IoTComputer Networks and CommunicationsComputer scienceDecision treeChannel occupancy; cluster analysis; IoT; LoRa; LoRaWAN; machine learning; network optimization; prediction analysisMachine learningcomputer.software_genreChannel occupancyLoRalcsh:QA75.5-76.95network optimizationNetwork performanceProtocol (object-oriented programming)Profiling (computer programming)Artificial neural networkNetwork packetbusiness.industrySettore ING-INF/03 - TelecomunicazioniPipeline (software)LoRaWANHuman-Computer Interactionmachine learningprediction analysisArtificial intelligencelcsh:Electronic computers. Computer sciencebusinesscomputerCommunication channelcluster analysis
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