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Toplam kayıt 5, listelenen: 1-5
Metabolic Imaging Based Sub-Classification of Lung Cancer
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA, 2020)
Lung cancer is one of the deadliest cancer types whose 84% is non-small cell lung cancer (NSCLC). In this study, deep learning-based classification methods were investigated comprehensively to differentiate two subtypes ...
Lung cancer subtype differentiation from positron emission tomography images
(TUBITAK SCIENTIFIC & TECHNICAL RESEARCH COUNCIL TURKEY, ATATURK BULVARI NO 221, KAVAKLIDERE, ANKARA, 00000, TURKEY, 2020)
Lung cancer is one of the deadly cancer types, and almost 85% of lung cancers are nonsmall cell lung cancer (NSCLC). In the present study we investigated classification and feature selection methods for the differentiation ...
Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge
(NATURE RESEARCHHEIDELBERGER PLATZ 3, BERLIN 14197, GERMANY, 2021)
Consumer wearables and sensors are a rich source of data about patients' daily disease and symptom burden, particularly in the case of movement disorders like Parkinson's disease (PD). However, interpreting these complex ...
A Continuously Benchmarked and Crowdsourced Challenge for Rapid Development and Evaluation of Models to Predict COVID-19 Diagnosis and Hospitalization
(AMER MEDICAL ASSOC330 N WABASH AVE, STE 39300, CHICAGO, IL 60611-5885, 2021)
IMPORTANCE Machine learning could be used to predict the likelihood of diagnosis and severity of illness. Lack of COVID-19 patient data has hindered the data science community in developing models to aid in the response ...
Effect of interpolation on specular reflections in texture-based automatic colonic polyp detection
(WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA, 2020)
Reflections of LED light cause unwanted noise effects called specular reflection (SR) on colonoscopic images. The aim of this study was to seek answers to the following two questions. (a) How are the texture features used ...