Prediction of the human papillomavirus status in patients with oropharyngeal squamous cell carcinoma by FDG-PET imaging dataset using deep learning analysis: A hypothesis-generating study.
Sign Up to like & getrecommendations! Published in 2020 at "European journal of radiology"
DOI: 10.1016/j.ejrad.2020.108936
Abstract: PURPOSE To assess the diagnostic accuracy of imaging-based deep learning analysis to differentiate between human papillomavirus (HPV) positive and negative oropharyngeal squamous cell carcinomas (OPSCCs) using FDG-PET images. METHODS One hundred and twenty patients with… read more here.
Keywords: status; learning analysis; deep learning; fdg pet ... See more keywords
A space for learning: An analysis of research on active learning spaces
Sign Up to like & getrecommendations! Published in 2019 at "Heliyon"
DOI: 10.1016/j.heliyon.2019.e02967
Abstract: Active Learning Classrooms (ALCs) are learning spaces specially designed to optimize the practice of active learning and amplify its positive effects in learners from young children through university-level learners. As interest in and adoption of… read more here.
Keywords: learning analysis; active learning; research; space learning ... See more keywords
Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa.
Sign Up to like & getrecommendations! Published in 2019 at "Magnetic resonance imaging"
DOI: 10.1016/j.mri.2019.05.017
Abstract: PURPOSE To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis… read more here.
Keywords: learning analysis; machine learning; mri derived; analysis ... See more keywords
Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor type
Sign Up to like & getrecommendations! Published in 2021 at "Translational Oncology"
DOI: 10.1016/j.tranon.2021.101016
Abstract: Highlights • CUP occurs in as many as 3–5% of patients when standard diagnostic tests are not able to determine the origin of cancer.• MI GPSai (Genomic Prevalence Score) is an AI that uses genomic… read more here.
Keywords: genomic transcriptomic; learning analysis; machine learning; tumor type ... See more keywords
Diurnal Changes and Machine Learning Analysis of Perovskite Modules Based on Two Years of Outdoor Monitoring
Sign Up to like & getrecommendations! Published in 2024 at "ACS Energy Letters"
DOI: 10.1021/acsenergylett.4c01943
Abstract: Long-term stability is the primary challenge for the commercialization of perovskite photovoltaics, exacerbated by limited outdoor data and unclear correlations between indoor and outdoor tests. In this study, we report on the outdoor stability testing… read more here.
Keywords: changes machine; analysis; machine learning; diurnal changes ... See more keywords
Deep Learning Analysis of Polaritonic Wave Images.
Sign Up to like & getrecommendations! Published in 2021 at "ACS nano"
DOI: 10.1021/acsnano.1c07011
Abstract: Deep learning (DL) is an emerging analysis tool across the sciences and engineering. Encouraged by the successes of DL in revealing quantitative trends in massive imaging data, we applied this approach to nanoscale deeply subdiffractional… read more here.
Keywords: learning analysis; polaritonic wave; analysis; deep learning ... See more keywords
Machine Learning for Analysis of Time-Resolved Luminescence Data
Sign Up to like & getrecommendations! Published in 2018 at "ACS Photonics"
DOI: 10.1021/acsphotonics.8b01047
Abstract: Time-resolved photoluminescence is one of the most standard techniques to understand and systematically optimize the performance of optical materials and optoelectronic devices. Here, we present a ... read more here.
Keywords: learning analysis; machine learning; analysis time; time ... See more keywords
Data-driven optimization and machine learning analysis of compatible molecules for halide perovskite material
Sign Up to like & getrecommendations! Published in 2024 at "npj Computational Materials"
DOI: 10.1038/s41524-024-01297-4
Abstract: Optoelectronic stability of halide perovskite material in hostile conditions such as water is rather limited, preventing them from further industrial deployment. Here, we optimize and perform machine learning analysis on CH_3NH_3PbI_3 materials with additives, solvents… read more here.
Keywords: perovskite material; machine learning; machine; data driven ... See more keywords
Machine learning analysis of the effects of COVID-19 on migration patterns
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-80841-0
Abstract: This study investigates the impact of the COVID-19 pandemic on European tourist mobility patterns from 2019 to 2021 by conceptualizing countries as monomers emitting radiation to model and analyze their patterns through the lens of… read more here.
Keywords: mobility patterns; mobility; machine learning; analysis effects ... See more keywords
Machine Learning Analysis to Classify Nanoparticles from Noisy spICP-TOFMS Data
Sign Up to like & getrecommendations! Published in 2023 at "Journal of Analytical Atomic Spectrometry"
DOI: 10.1039/d3ja00081h
Abstract: Single-particle inductively coupled plasma time-of-flight mass spectrometry (spICP-TOFMS) is a promising method for the quantification and classification of anthropogenic and natural nanoparticle (NP) types based on measured multi-elemental compositions of... read more here.
Keywords: nanoparticles noisy; classify nanoparticles; analysis classify; machine learning ... See more keywords
Feature Learning and Analysis for Cleanliness Classification in Restrooms
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2894006
Abstract: In order to revamp the cleaning contract from the head-count basis into a performance basis, a fair and unbiased cleanliness classification is necessary. However, the perception of cleanliness is very subjective to the observer. Hence,… read more here.
Keywords: cleanliness; feature learning; cleanliness classification; analysis ... See more keywords