0000000000810037

AUTHOR

S. Sarker

showing 2 related works from this author

RANDOMIZED PHASE II STUDY OF FIRST-LINE EVEROLIMUS (EVE) + BEVACIZUMAB (BEV) VERSUS INTERFERON ALFA-2A (IFN) + BEV IN PATIENTS (PTS) WITH METASTATIC …

2012

ABSTRACT Background Study results demonstrated that IFN augments BEV activity and improves median PFS in pts with mRCC. Thus, combination BEV + IFN is a standard first-line treatment option for mRCC. Combining BEV with the mTOR inhibitor EVE may be an efficacious and well-tolerated treatment option. The open-label, phase II RECORD-2 trial compared first-line EVE + BEV and IFN + BEV in mRCC. Patients and methods: Therapy-naive pts with clear cell mRCC and prior nephrectomy were randomized 1:1 to BEV 10 mg/kg IV every 2 weeks with either EVE 10 mg oral daily or IFN (9 MIU SC 3 times/week, if tolerated). Tumour assessments were every 12 weeks. Primary objective was treatment effect on progress…

medicine.medical_specialtymedicine.medical_treatmentGastroenterology03 medical and health sciences0302 clinical medicineProstateInternal medicinemedicineStomatitisObjective response030304 developmental biology0303 health sciencesProteinuriaGenitourinary systembusiness.industryTreatment optionsHematologymedicine.diseaseNephrectomy3. Good healthmedicine.anatomical_structureOncologyTolerability030220 oncology & carcinogenesismedicine.symptombusinessAnnals of Oncology
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A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory

2021

Continued improvements on existing reconstruction methods are vital to the success of high-energy physics experiments, such as the IceCube Neutrino Observatory. In IceCube, further challenges arise as the detector is situated at the geographic South Pole where computational resources are limited. However, to perform real-time analyses and to issue alerts to telescopes around the world, powerful and fast reconstruction methods are desired. Deep neural networks can be extremely powerful, and their usage is computationally inexpensive once the networks are trained. These characteristics make a deep learning-based approach an excellent candidate for the application in IceCube. A reconstruction …

FOS: Computer and information sciencesComputer Science - Machine LearningAstrophysics::High Energy Astrophysical Phenomenacs.LGData analysisFOS: Physical sciencesFitting methods01 natural sciencesConvolutional neural networkCalibration; Cluster finding; Data analysis; Fitting methods; Neutrino detectors; Pattern recognitionHigh Energy Physics - ExperimentIceCube Neutrino ObservatoryMachine Learning (cs.LG)High Energy Physics - Experiment (hep-ex)Pattern recognition0103 physical sciencesNeutrino detectors010303 astronomy & astrophysicsInstrumentationMathematical Physics010308 nuclear & particles physicsbusiness.industryhep-exDeep learningCluster findingDetectorNeutrino detectorComputer engineeringOrders of magnitude (time)13. Climate actionCascadeCalibrationPattern recognition (psychology)Artificial intelligencebusiness
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