Search results for "3211 Oncology and Carcinogenesis"

showing 3 items of 3 documents

The international WAO/EAACI guideline for the management of hereditary angioedema – the 2017 revision and update

2018

Hereditary Angioedema (HAE) is a rare and disabling disease. Early diagnosis and appropriate therapy are essential. This update and revision of the global guideline for HAE provides up-to-date consensus recommendations for the management of HAE. In the development of this update and revision of the guideline, an international expert panel reviewed the existing evidence and developed 20 recommendations that were discussed, finalized and consented during the guideline consensus conference in June 2016 in Vienna. The final version of this update and revision of the guideline incorporates the contributions of a board of expert reviewers and the endorsing societies. The goal of this guideline up…

MaleAftercare32 Biomedical and Clinical SciencesLanadelumabC1-inhibitorDiseaseGuidelineRecommendations0302 clinical medicinePregnancyDiagnosisImmunology and Allergy030212 general & internal medicinePrecision MedicineChildHereditary angioedemaConsensus conferenceSelf-administrationManagementGRADEHereditary angioedemaFemaleComplement C1 Inhibitor ProteinQuality of lifeAdultPulmonary and Respiratory Medicinemedicine.medical_specialtyWhat treatmentConsensusAdolescentHealth Planning GuidelinesImmunologyMEDLINEDysfunctional family7.3 Management and decision makingYoung Adult03 medical and health sciencesRare DiseasesQuality of life (healthcare)Clinical ResearchTerminology as TopicIndividualized therapymedicineHumansLactationFinal versionProphylaxisbusiness.industryPreventionAngioedemas HereditaryGuidelinePrecision medicinemedicine.disease3211 Oncology and Carcinogenesis030228 respiratory systemFamily medicineTherapybusiness7 Management of diseases and conditions
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A phase I dose escalation and expansion study of the next generation oral SERD AZD9833 in women with ER-positive, HER2-negative advanced breast cancer

2020

1024 Background: AZD9833 is an oral selective estrogen receptor (ER) antagonist and degrader (SERD) that has shown antitumor efficacy in a range of preclinical models of breast cancer. Methods: SERENA-1 (NCT03616587) is an ongoing Phase 1, open-label study in pre- and post-menopausal women, after ≥1 endocrine therapy and ≤2 prior chemotherapies for ER+ HER2- advanced breast cancer (ABC). The primary objective is to determine the safety and tolerability of AZD9833 once daily (QD), with dose-limiting toxicities (DLTs) in 28d defining the maximum tolerated dose. Secondary objectives include pharmacokinetics and anti-tumor response. Pharmacodynamic (PD) analysis includes ER modulation in paire…

OncologyCancer Researchmedicine.medical_specialtyAdvanced breastClinical Trials and Supportive ActivitiesEstrogen receptor32 Biomedical and Clinical Sciences6 Evaluation of treatments and therapeutic interventions03 medical and health sciences0302 clinical medicineBreast cancerClinical ResearchInternal medicineBreast CancerDose escalationMedicineCancerbusiness.industryAntagonistHER2 negativeCancermedicine.disease3211 Oncology and CarcinogenesisOncology030220 oncology & carcinogenesis6.1 Pharmaceuticalsbusiness030215 immunology
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CNN-Based Prostate Zonal Segmentation on T2-Weighted MR Images: A Cross-Dataset Study

2020

Prostate cancer is the most common cancer among US men. However, prostate imaging is still challenging despite the advances in multi-parametric magnetic resonance imaging (MRI), which provides both morphologic and functional information pertaining to the pathological regions. Along with whole prostate gland segmentation, distinguishing between the central gland (CG) and peripheral zone (PZ) can guide toward differential diagnosis, since the frequency and severity of tumors differ in these regions; however, their boundary is often weak and fuzzy. This work presents a preliminary study on deep learning to automatically delineate the CG and PZ, aiming at evaluating the generalization ability o…

Urologic DiseasesComputer scienceContext (language use)32 Biomedical and Clinical Sciences-Convolutional neural networkDeep convolutional neural networks Prostate zonal segmentation Cross-dataset generalizationProstate cancer46 Information and Computing SciencesProstateDeep convolutional neural networksmedicineAnatomical MRISegmentationProstate zonal segmentation; Prostate cancer; Anatomical MRI; Deep convolutional neural networks; Cross-dataset generalization;3202 Clinical SciencesCancerSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniProstate cancerSettore INF/01 - Informaticamedicine.diagnostic_testbusiness.industryDeep learningINF/01 - INFORMATICAMagnetic resonance imagingPattern recognitionmedicine.disease3211 Oncology and Carcinogenesismedicine.anatomical_structureCross-dataset generalizationProstate zonal segmentationBiomedical ImagingArtificial intelligenceDeep convolutional neural networkbusinessT2 weightedAnatomical MRI; Cross-dataset generalization; Deep convolutional neural networks; Prostate cancer; Prostate zonal segmentation
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