Causality-driven candidate identification for reliable DNA methylation biomarker discovery by Xinlu Tang, Rui Guo, Zhanfeng Mo, Wenli Fu, Xiaohua Qian

“…Overall, this study offers a causal-deep-learning-based perspective with a compatible tool to identify reliable DNAm biomarker candidates, promoting resource-efficient biomarker discovery.…”
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A Time-Aware CNN-Based Personalized Recommender System by Dan Yang, Jing Zhang, Sifeng Wang, XueDong Zhang

“…With the in-depth study and application of deep learning algorithms, deep neural network is gradually used in recommender systems. …”
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DNA promoter task-oriented dictionary mining and prediction model based on natural language technology by Ruolei Zeng, Zihan Li, Jialu Li, Qingchuan Zhang

“…Recent advancements in bioinformatics have leveraged deep learning and natural language processing (NLP) to enhance promoter prediction accuracy. …”
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Kontrol Level Kecepatan Kipas Melalui Deteksi Gestur Jari Tangan Menggunakan MediaPipe dan Faster-RCNN by Muhammad Aldi Fakhruddin, Heri Pratikno, Musayyanah, Weny Indah Kusumawati

“…Mikrokontroler yang digunakan pada penelitian ini adalah Arduino Uno, sedangkan penerapan computer vision for deep learning menggunakan framework MediaPipe dan Faster-RCNN. …”
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NuFold: end-to-end approach for RNA tertiary structure prediction with flexible nucleobase center representation by Yuki Kagaya, Zicong Zhang, Nabil Ibtehaz, Xiao Wang, Tsukasa Nakamura, Pranav Deep Punuru, Daisuke Kihara

“…To address this challenge, we developed NuFold, a novel computational approach that leverages state-of-the-art deep learning architecture to accurately predict RNA tertiary structures. …”
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Optimized digital workflow for pathologist-grade evaluation in bleomycin-induced pulmonary fibrosis mouse model by Toshiki Goto, Akira Sano, Shinichi Onishi, Natsuko Hada, Rui Kimata, Saori Matsuo, Sohei Oyama, Atsuhiko Kato, Hideaki Mizuno, Masaki Yamazaki

“…Therefore, we developed a new workflow for BLM model that reduces inter- and intra-observer variations and improves the evaluation process. We generated deep learning models for grading lung fibrosis that were able to achieve accuracy comparable to that of pathologists. …”
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A Joint Deep Recommendation Framework for Location-Based Social Networks by Omer Tal, Yang Liu

“…In addition, we provide further insight into the design selections and hyperparameters of our recommender system, hoping to shed light on the benefit of deep learning for location-based social network recommendation.…”
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Adaptive genetic algorithm based deep feature selector for cancer detection in lung histopathological images by Avigyan Roy, Priyam Saha, Nandita Gautam, Friedhelm Schwenker, Ram Sarkar

“…Convolutional neural network based pretrained deep learning models can be used successfully to detect lung cancer. …”
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Research on the improvement method of imbalance of ground penetrating radar image data by Ligang Cao, Lei Liu, Congde Lu, Ruimin Chen

“…This leads to poor accuracy of deep learning for injury classification. And the cost of collecting a large amount of data in the field is higher. …”
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Predicting and synthesizing terahertz spoof surface plasmon polariton devices with a convolutional neural network model by Vahid Najafy, Bijan Abbasi-Arand, Maryam Hesari-Shermeh

“…Abstract With the increasing global attention to deep learning and the advancements made in applying convolutional neural networks in electromagnetics, we have recently witnessed the utilization of deep learning-based networks for predicting the spectrum and electromagnetic properties of structures instead of traditional tools like fully numerical-based methods. …”
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Review of communication optimization methods in federated learning by YANG Zhikai, LIU Yaping, ZHANG Shuo, SUN Zhe, YAN Dingyu

“…With the development and popularization of artificial intelligence technologies represented by deep learning, the security issues they continuously expose have become a huge challenge affecting cyberspace security. …”
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Integrating Macroeconomic and Technical Indicators into Forecasting the Stock Market: A Data-Driven Approach by Saima Latif, Faheem Aslam, Paulo Ferreira, Sohail Iqbal

“…We propose three hybrid deep learning models that sequentially combine convolutional and recurrent neural networks for improved feature extraction and predictive accuracy. …”
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Optimized sequential model for superior classification of plant disease by Yogesh Chimate, Sangram Patil, K. Prathapan, Jaydeep Patil, Jayendra Khot

“…Deep learning architectures, like convolutional neural network, can autonomously learn and extract complicated characteristics and patterns from huge datasets. …”
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Optimalisasi Hyper Parameter Convolutional Neural Networks Menggunakan Ant Colony Optimization by Fian Yulio Santoso, Eko Sediyono, Hindriyanto Dwi Purnomo

“…Salah satu metode tersebut menggabungkan convolutional neural networks (CNN) dengan deep learning, tetapi hyperparameter, seperti fungsi loss, fungsi aktivasi, dan optimizers, memengaruhi kinerjanya. …”
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Comparative use of different AI methods for the prediction of concrete compressive strength by Mouhamadou Amar

“…The most accurate model was found to be a gradient-boosted tree followed by deep learning and random forest. Forecasts were validated with high accuracy by comparing experimental results to numerical data.…”
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Improving Medical Image Quality Using a Super-Resolution Technique with Attention Mechanism by Dong Yun Lee, Jang Yeop Kim, Soo Young Cho

“…The model uses L1 loss to generate realistic and smooth outputs, outperforming existing deep learning methods in capturing contours and textures. …”
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An Attention-Based Multidimensional Fault Information Sharing Framework for Bearing Fault Diagnosis by Yunjin Hu, Qingsheng Xie, Xudong Yang, Hai Yang, Yizong Zhang

“…Deep learning has performed well in feature extraction and pattern recognition and has been widely studied in the field of fault diagnosis. …”
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Detection of cervical cell based on multi-scale spatial information by Gang Li, Xinyu Fan, Chuanyun Xu, Pengfei Lv, Ru Wang, Zihan Ruan, Zheng Zhou, Yang Zhang

“…Abstract Cervical cancer poses a significant health risk to women. Deep learning methods can assist pathologists in quickly screening images of suspected lesion cells, greatly improving the efficiency of cervical cancer screening and diagnosis. …”
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A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN by Afuan Lasmedi, Isnanto R. Rizal

“…Additionally, this research opens avenues for optimizing deep learning models and leveraging edge computing technologies to reduce response times in wearable device applications.…”
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Ancient Stone Inscription Image Denoising and Inpainting Methods Based on Deep Neural Networks by Haoming Zhang, Yue Qi, Xiaoting Xue, Yahui Nan

“…For ancient stone inscriptions, we should obtain more perfect digital results without multiple types of noise, while there are few deep learning methods designed for processing stone inscription images. …”
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