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Bibliographics

This is a table of authors, titles, dates and other bibliographic information; it is a list metadata describing the content of your study carrel. Think of it as your library.

id author title date words sentences text
cord-334495-7y1la856Agricola, EustachioHeart and Lung Multimodality Imaging in COVID-192020-06-246791325view text
cord-006708-nionk55wAktaş, FatmaThe pulmonary findings of Crimean–Congo hemorrhagic fever patients with chest X-ray assessments2019-03-253583212view text
cord-266672-t85wd0xqBagnera, SilviaPerformance of Radiologists in the Evaluation of the Chest Radiography with the Use of a “new software score” in Coronavirus Disease 2019 Pneumonia Suspected Patients2020-07-203053137view text
cord-310228-bqpvykceBorkowski, A. A.Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis2020-05-263193216view text
cord-167889-um3djluzChen, JianguoA Survey on Applications of Artificial Intelligence in Fighting Against COVID-192020-07-0412248768view text
cord-292341-uo54ghf3Cocconcelli, ElisabettaClinical Features and Chest Imaging as Predictors of Intensity of Care in Patients with COVID-192020-09-165195249view text
cord-006683-7rsmbk3jCoppola, M.Influenza A virus: radiological and clinical findings of patients hospitalised for pandemic H1N1 influenza2011-01-124838374view text
cord-337507-cqbbrnkuCozzi, AndreaChest x-ray in the COVID-19 pandemic: Radiologists’ real-world reader performance2020-09-102594114view text
cord-331891-a6b1xanmCozzi, DilettaChest X-ray in new Coronavirus Disease 2019 (COVID-19) infection: findings and correlation with clinical outcome2020-06-092916144view text
cord-336843-c0sr3sixGerritsen, M. G.Improving early diagnosis of pulmonary infections in patients with febrile neutropenia using low-dose chest computed tomography2017-02-244321239view text
cord-296208-uy1r6lt2Greenspan, HayitPosition paper on COVID-19 imaging and AI: from the clinical needs and technological challenges to initial AI solutions at the lab and national level towards a new era for AI in healthcare2020-08-198008395view text
cord-018027-goxdiyv3Heussel, Claus PeterDiagnostic Radiology in Hematological Patients with Febrile Neutropenia2014-11-274904306view text
cord-346942-88l03lf0Kerpel, ArielDiagnostic and Prognostic Value of Chest Radiographs for COVID-19 at Presentation2020-08-174481248view text
cord-297198-dneycnyrKhan, T.Re: a British Society of Thoracic Imaging statement: considerations in designing local imaging diagnostic algorithms for the COVID-19 pandemic2020-05-2764461view text
cord-347691-ia2i8svgLarici, Anna RitaMultimodality imaging of COVID-19 pneumonia: from diagnosis to follow-up. A comprehensive review2020-08-177456363view text
cord-103840-2diao7zhMungai, B. N.It''s not TB but what could it be? Abnormalities on chest X-rays taken during the Kenya National Tuberculosis Prevalence Survey2020-08-225916356view text
cord-157444-huvnyaliNabulsi, ZaidDeep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases2020-10-226802326view text
cord-297396-r1p7xn3aNg, Ming-YenDevelopment and Validation of Risk Prediction Models for COVID-19 Positivity in a Hospital Setting2020-09-153251182view text
cord-028786-400vglzmOloko-Oba, MustaphaDiagnosing Tuberculosis Using Deep Convolutional Neural Network2020-06-052438118view text
cord-282198-ugmv9om1Pare, Joseph R.Point-of-care Lung Ultrasound Is More Sensitive than Chest Radiograph for Evaluation of COVID-192020-06-193406193view text
cord-355218-eici4eitPunn, Narinder SinghAutomated diagnosis of COVID-19 with limited posteroanterior chest X-ray images using fine-tuned deep neural networks2020-10-175950324view text
cord-127759-wpqdtdjsQi, XiaoChest X-ray Image Phase Features for Improved Diagnosis of COVID-19 Using Convolutional Neural Network2020-11-063896250view text
cord-013065-oj0wsstzRodríguez-Fanjul, JavierProcalcitonin and lung ultrasound algorithm to diagnose severe pneumonia in critical paediatric patients (PROLUSP study). A randomised clinical trial2020-10-083735225view text
cord-303483-wendrxeeRubin, Geoffrey D.The Role of Chest Imaging in Patient Management during the COVID-19 Pandemic: A Multinational Consensus Statement from the Fleischner Society2020-04-074315189view text
cord-275974-uqd30v7bShorfuzzaman, MohammadMetaCOVID: A Siamese neural network framework with contrastive loss for n-shot diagnosis of COVID-19 patients2020-10-175429268view text
cord-350636-ufwfitueShumilov, EvgeniiComparison of Chest Ultrasound and Standard X-Ray Imaging in COVID-19 Patients2020-09-022368137view text
cord-294557-4h0sybiyStogiannos, N.Coronavirus disease 2019 (COVID-19) in the radiology department: What radiographers need to know2020-06-046725377view text
cord-312251-t6omrr07Vancheri, Sergio GiuseppeRadiographic findings in 240 patients with COVID-19 pneumonia: time-dependence after the onset of symptoms2020-05-303502189view text
cord-269014-ck27fm58Vo, Luan Nguyen QuangEnhanced Private Sector Engagement for Tuberculosis Diagnosis and Reporting through an Intermediary Agency in Ho Chi Minh City, Viet Nam2020-09-145040238view text
cord-345528-rk16pt0iYasar, Y.MantisCOVID: Rapid X-Ray Chest Radiograph and Mortality Rate Evaluation With Artificial Intelligence For COVID-192020-05-083173198view text
cord-238881-tupom7fbYeh, Chun-FuA Cascaded Learning Strategy for Robust COVID-19 Pneumonia Chest X-Ray Screening2020-04-243356179view text
cord-327257-doygrgrcZhu, JocelynDeep transfer learning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs2020-07-283686221view text
cord-015352-2d02eq3ynanESPR 20172017-04-26822534479view text