Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study by Songjing Chen, Sizhu Wu

“…For each subgroup, random forest, extreme gradient boosting, deep neural networks, support vector machine, multiple logistic regression and deep Q network (DQN) models were developed and validated. …”
Get full text

Bioinformatics and Deep Learning Approach to Discover Food-Derived Active Ingredients for Alzheimer’s Disease Therapy by Junyu Zhou, Chen Li, Yong Kwan Kim, Sunmin Park

“…In conclusion, our findings demonstrate the efficacy of combining bioinformatics with deep neural networks to expedite the discovery of previously unidentified food-derived active ingredients (NCs) for AD intervention.…”
Get full text

A Parallel Image Denoising Network Based on Nonparametric Attention and Multiscale Feature Fusion by Jing Mao, Lianming Sun, Jie Chen, Shunyuan Yu

“…The proposed method provided a new idea for the study of deep neural networks in the field of image denoising.…”
Get full text

Progressive Self-Prompting Segment Anything Model for Salient Object Detection in Optical Remote Sensing Images by Xiaoning Zhang, Yi Yu, Daqun Li, Yuqing Wang

“…With the continuous advancement of deep neural networks, salient object detection (SOD) in natural images has made significant progress. …”
Get full text

Efficient Method for Robust Backdoor Detection and Removal in Feature Space Using Clean Data by Donik Vrsnak, Marko Subasic, Sven Loncaric

“…The steady increase of proposed backdoor attacks on deep neural networks highlights the need for robust defense methods for their detection and removal. …”
Get full text

Investigating Maps of Science Using Contextual Proximity of Citations Based on Deep Contextualized Word Representation by Muhammad Roman, Abdul Shahid, Shafiullah Khan, Lisu Yu, Muhammad Asif, Yazeed Yasin Ghadi

“…We have, therefore, used contextual word representation, which is trained through deep neural networks. Deep models require massive data for generalizing the model, however, the existing state-of-the-art datasets don’t provide much information for the training models to get generalized. …”
Get full text

Harnessing deep learning to detect bronchiolitis obliterans syndrome from chest CT by Mateusz Koziński, Doruk Oner, Jakub Gwizdała, Catherine Beigelman-Aubry, Pascal Fua, Angela Koutsokera, Alessio Casutt, Argyro Vraka, Michele De Palma, John-David Aubert, Horst Bischof, Christophe von Garnier, Sahand Jamal Rahi, Martin Urschler, Nahal Mansouri

“…Abstract Background Bronchiolitis Obliterans Syndrome (BOS), a fibrotic airway disease that may develop after lung transplantation, conventionally relies on pulmonary function tests (PFTs) for diagnosis due to limitations of CT imaging. Deep neural networks (DNNs) have not previously been used for BOS detection. …”
Get full text

A fast monocular 6D pose estimation method for textureless objects based on perceptual hashing and template matching by Jose Moises Araya-Martinez, Jose Moises Araya-Martinez, Vinicius Soares Matthiesen, Vinicius Soares Matthiesen, Simon Bøgh, Jens Lambrecht, Rui Pimentel de Figueiredo

“…Many state-of-the-art methods for 6D pose estimation depend on deep neural networks, which are computationally demanding and require GPUs for real-time performance. …”
Get full text

AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE by X. Wang, L. Bi, H. Wang, Y. Wang, W. Han, X. Shen, X. Zhang

“…To obtain AI-NAOS, a database of the optical properties for the models was constructed using the invariant imbedding T-matrix method (IITM), and deep neural networks (DNN) were trained based on this database. …”
Get full text

4D Radar Imaging and Camera Fusion for Road Crossing Detection and Classification Using Deep Learning by Liyaana Shahirah Wan Abd Aziz, Farah Nadia Mohd Isa, Faridah Abd Rahman, Arvind Hari Narayanan, Ahmad Reza Alghooneh, George Shaker

“…The system utilizes deep neural networks implemented via Keras and TensorFlow to detect and classify multiple targets, including pedestrians, cars, buses, and trucks. …”
Get full text