Multitask Deep Neural Networks for Ames Mutagenicity Prediction
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c00532
Abstract: The Ames mutagenicity test constitutes the most frequently used assay to estimate the mutagenic potential of drug candidates. While this test employs experimental results using various strains of Salmonella typhimurium, the vast majority of the… read more here.
Keywords: neural networks; multitask; ames mutagenicity; deep neural ... See more keywords
Multitask Deep Ensemble Prediction of Molecular Energetics in Solution: From Quantum Mechanics to Experimental Properties.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.2c01024
Abstract: The past few years have witnessed significant advances in developing machine learning methods for molecular energetics predictions, including calculated electronic energies with high-level quantum mechanical methods and experimental properties, such as solvation free energy and… read more here.
Keywords: deep ensemble; molecular energetics; sphysnet ens5; experimental properties ... See more keywords
A multimodal multitask deep learning framework for vibrotactile feedback and sound rendering
Sign Up to like & getrecommendations! Published in 2024 at "Scientific Reports"
DOI: 10.1038/s41598-024-64376-y
Abstract: Data-driven approaches are often utilized to model and generate vibrotactile feedback and sounds for rigid stylus-based interaction. Nevertheless, in prior research, these two modalities were typically addressed separately due to challenges related to synchronization and… read more here.
Keywords: deep learning; multitask deep; multimodal multitask; framework ... See more keywords
Multiscale Multitask Deep NetVLAD for Crowd Counting
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Industrial Informatics"
DOI: 10.1109/tii.2018.2852481
Abstract: Deep convolutional networks (CNNs) reign undisputed as the new de-facto method for computer vision tasks owning to their success in visual recognition task on still images. However, their adaptations to crowd counting have not clearly… read more here.
Keywords: crowd; multitask deep; deep netvlad; crowd counting ... See more keywords
Multitask Deep Learning for Segmentation and Classification of Primary Bone Tumors on Radiographs.
Sign Up to like & getrecommendations! Published in 2021 at "Radiology"
DOI: 10.1148/radiol.2021204531
Abstract: Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and classification… read more here.
Keywords: bone tumors; classification; multitask deep; primary bone ... See more keywords
A Multitask Deep Learning Framework for DNER
Sign Up to like & getrecommendations! Published in 2022 at "Computational Intelligence and Neuroscience"
DOI: 10.1155/2022/3321296
Abstract: Over the years, the explosive growth of drug-related text information has resulted in heavy loads of work for manual data processing. However, the domain knowledge hidden is believed to be crucial to biomedical research and… read more here.
Keywords: framework dner; deep learning; multitask deep; dner ... See more keywords
Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study
Sign Up to like & getrecommendations! Published in 2025 at "BMC Medical Informatics and Decision Making"
DOI: 10.1186/s12911-025-03050-3
Abstract: Prognostic prediction is crucial to guide individual treatment for patients with rectal cancer. We aimed to develop and validated a multitask deep learning model for predicting prognosis in rectal cancer patients. This retrospective study enrolled… read more here.
Keywords: deep learning; multitask deep; rectal cancer; learning model ... See more keywords