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Toplam kayıt 7, listelenen: 1-7
Structural profile matrices for predicting structural properties of proteins
(WORLD SCIENTIFIC PUBL CO PTE LTD, 5 TOH TUCK LINK, SINGAPORE 596224, SINGAPORE, 2020)
Predicting structural properties of proteins plays a key role in predicting the 3D structure of proteins. In this study, new structural profile matrices (SPM) are developed for protein secondary structure, solvent accessibility ...
Improved classification of colorectal polyps on histopathological images with ensemble learning and stain normalization
(ELSEVIER IRELAND, 2023)
Background and Objective: Early detection of colon adenomatous polyps is critically important because correct detection of it significantly reduces the potential of developing colon cancers in the future. The key challenge ...
IGPRED-MultiTask: A Deep Learning Model to Predict Protein Secondary Structure, Torsion Angles and Solvent Accessibility
(IEEE COMPUTER SOC, 2023)
Protein secondary structure, solvent accessibility and torsion angle predictions are preliminary steps to predict 3D structure of a protein. Deep learning approaches have achieved significant improvements in predicting ...
Comparative analysis of machine learning approaches for predicting respiratory virus infection and symptom severity
(PEERJ INC, 2023)
Respiratory diseases are among the major health problems causing a burden on hospitals. Diagnosis of infection and rapid prediction of severity without time-consuming clinical tests could be beneficial in preventing the ...
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 ...
An effective colorectal polyp classification for histopathological images based on supervised contrastive learning
(ELSEVIER, 2024)
Early detection of colon adenomatous polyps is pivotal in reducing colon cancer risk. In this context, accurately distinguishing between adenomatous polyp subtypes, especially tubular and tubulovillous, from hyperplastic ...