Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis by Mattijs Bulcaen, Ronald B. Liu, Kasper Gryspeert, Sam Thierie, Anabela S. Ramalho, François Vermeulen, Xavier Casadevall I Solvas, Marianne S. Carlon

“…Summary: Here, we present a protocol for the rapid functional screening of gene editing and addition strategies in patient-derived organoids using the deep-learning-based tool DETECTOR (detection of targeted editing of cystic fibrosis transmembrane conductance regulator [CFTR] in organoids). …”
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A Physics-Based Hyper Parameter Optimized Federated Multi-Layered Deep Learning Model for Intrusion Detection in IoT Networks by Chirag Jitendra Chandnani, Vedik Agarwal, Shlok Chetan Kulkarni, Aditya Aren, D. Geraldine Bessie Amali, Kathiravan Srinivasan

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AtOMICS: a deep learning-based automated optomechanical intelligent coupling system for testing and characterization of silicon photonics chiplets by Jaime Gonzalo Flor Flores, Jim Solomon, Connor Nasseraddin, Talha Yerebakan, Andrey B Matsko, Chee Wei Wong

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HIDRA3: a deep-learning model for multipoint ensemble sea level forecasting in the presence of tide gauge sensor failures by M. Rus, M. Rus, H. Mihanović, M. Ličer, M. Ličer, M. Kristan

“…A recently proposed deep-learning model, HIDRA2 (HIgh-performance Deep tidal Residual estimation method using Atmospheric data, version 2), avoids numerical simulations while delivering competitive forecasts. …”
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Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention by Fawaz Khaled Alarfaj, Shabnam Shahzadi

Subjects: “…Deep learning…”
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A Deep Learning Approach to Classify Fabry Cardiomyopathy from Hypertrophic Cardiomyopathy Using Cine Imaging on Cardiac Magnetic Resonance by Wei-Wen Chen, Ling Kuo, Yi-Xun Lin, Wen-Chung Yu, Chien-Chao Tseng, Yenn-Jiang Lin, Ching-Chun Huang, Shih-Lin Chang, Jacky Chung-Hao Wu, Chun-Ku Chen, Ching-Yao Weng, Siwa Chan, Wei-Wen Lin, Yu-Cheng Hsieh, Ming-Chih Lin, Yun-Ching Fu, Tsung Chen, Shih-Ann Chen, Henry Horng-Shing Lu

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Deep learning radiomics nomogram for preoperatively identifying moderate-to-severe chronic cholangitis in children with pancreaticobiliary maljunction: a multicenter study by Hui-min Mao, Kai-ge Chen, Bin Zhu, Wan-liang Guo, San-li Shi

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Deep learning-enhanced detection of road culverts in high-resolution digital elevation models: Improving stream network accuracy in Sweden by William Lidberg

“…This study presents a novel method where a unique dataset of 28,512 culverts was used to develop a deep learning method to map road culverts, enabling the correction of digital elevation models and enhancing the accuracy of topographically derived stream networks. …”
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Estimating the Severity of Oral Lesions Via Analysis of Cone Beam Computed Tomography Reports: A Proposed Deep Learning Model by Sare Mahdavifar, Seyed Mostafa Fakhrahmad, Elham Ansarifard

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A Deep Learning-Based Approach for Two-Phase Flow Pattern Classification Using Void Fraction Time Series Analysis by Jefferson Dos Santos Ambrosio, Marco Jose da Silva, Andre Eugenio Lazzaretti

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Prediction of case types from non-searchable pdf documents in arabic: Comparison of machine learning and deep learning with image processing by El Arrasse Mouad, Khourdifi Youness, Mounir Soufyane, El Alami Alae

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A deep learning approach for automatic 3D segmentation of hip cartilage and labrum from direct hip MR arthrography by Malin Kristin Meier, Ramon Andreas Helfenstein, Adam Boschung, Andreas Nanavati, Adrian Ruckli, Till D. Lerch, Nicolas Gerber, Bernd Jung, Onur Afacan, Moritz Tannast, Klaus A. Siebenrock, Simon D Steppacher, Florian Schmaranzer

“…When tested on the external dataset, the DSC was 0.89 ± 0.02 (0.88–0.90) and 0.71 ± 0.04 (0.69–0.73) for cartilage and labrum, respectively.The presented deep learning approach accurately segments hip cartilage and labrum from 3D MRI sequences and can potentially be used in clinical practice to provide rapid and accurate 3D MRI models.…”
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Estimating ocean currents from the joint reconstruction of absolute dynamic topography and sea surface temperature through deep learning algorithms by D. Ciani, C. Fanelli, B. Buongiorno Nardelli

“…To address these issues, we developed and tested different deep learning methodologies, specifically convolutional neural network (CNN) models that were originally proposed for single-image super resolution. …”
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Deep learning reconstruction of zero-echo time sequences to improve visualization of osseous structures and associated pathologies in MRI of cervical spine by Malwina Kaniewska, Fabio Zecca, Carina Obermüller, Falko Ensle, Eva Deininger-Czermak, Maelene Lohezic, Roman Guggenberger

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Multimodal marvels of deep learning in medical diagnosis using image, speech, and text: A comprehensive review of COVID-19 detection by Md Shofiqul Islam, Khondokar Fida Hasan, Hasibul Hossain Shajeeb, Humayan Kabir Rana, Md. Saifur Rahman, Md. Munirul Hasan, AKM Azad, Ibrahim Abdullah, Mohammad Ali Moni

Subjects: “…Deep learning…”
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Integration of ground-based and remote sensing data with deep learning algorithms for mapping habitats in Natura 2000 protected oak forests by Lucia Čahojová, Ivan Jarolímek, Barbora Klímová, Michal Kollár, Michaela Michalková, Karol Mikula, Aneta A. Ožvat, Denisa Slabejová, Mária Šibíková

“…This study aims to combine ground-based and remote sensing data utilising deep learning techniques to map protected forest habitats and communities within the Natura 2000 network. …”
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Feasibility of generating sagittal radiographs from coronal views using GAN-based deep learning framework in adolescent idiopathic scoliosis by Tito Bassani, Andrea Cina, Fabio Galbusera, Andrea Cazzato, Maria Elena Pellegrino, Domenico Albano, Luca Maria Sconfienza

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Accurate recognition of micromorphology images of epoxy coatings for deep-sea environments based on a deep learning super-resolution method by JiaQi Pan, Furou Liu, Jia Feng, Fandi Meng, Yufan Chen, Jianning Chi, Zelan Li, Jie Li, Li Liu

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Circle chaotic map tuna swarm optimization (CCMTSO) based feature selection and deep learning approach for air quality prediction by Aradhyamatada Swamy, Rohitha U.M.

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Penerapan Blok SE-NET Pada Deep Learning Inceptionv3 untuk Meningkatkan Deteksi Penyakit Mpox pada Manusia by M. Bakhara Alief Rachman, Aliyah Kurniasih, Andika Sundawijaya, Ahlijati Nuraminah

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