CTA image segmentation method for intracranial aneurysms based on MGLIA net by Lijie Hou, Jian Zhang, Lihui Zhao, Ke Meng, Xin Feng

“…When faced with a new hospital acquired imaging modality, it is usually necessary to redesign and train the segmentation network. In response to this issue, this article proposes a more universal segmentation model and develops the GLIA Net algorithm (MGLIA Net model) based on MoblieNet, which can perform adaptive target segmentation on aneurysm images collected under different conditions. …”
Get full text

MRI-based brain tumor ensemble classification using two stage score level fusion and CNN models by Oussama Bouguerra, Bilal Attallah, Youcef Brik

“…In the second stage, ensemble learning algorithms like weighted sum, fuzzy rank, and majority vote are used to combine the scores from the trained models, enhancing prediction results. …”
Get full text

Identification of recurrences in women diagnosed with early invasive breast cancer using routinely collected data in England by Jake Probert, David Dodwell, John Broggio, Robert Coleman, Helen Marshall, Sarah C. Darby, Gurdeep S. Mannu

“…Methods We used a database compiled by the West Midlands Cancer Intelligence Unit during 1997–2011 to develop and train a deterministic algorithm to identify recurrences in routinely collected data (RCD) available within NHS England. …”
Get full text

Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting by Ubaid Ahmed, Anzar Mahmood, Ahsan Raza Khan, Levin Kuhlmann, Khurram Saleem Alimgeer, Sohail Razzaq, Imran Aziz, Amin Hammad

“…The proposed PBNN is trained and evaluated on two geographical datasets and compared with state-of-the-art techniques. …”
Get full text

Applying Optimized ANN Models to Estimate Dew Point Pressure of Gas Condensates by Luo Han, Saeed Sarvazizi

“…A total of 721 data points were employed to train and test the algorithm. In addition, the outlier data were identified and excluded. …”
Get full text

Validating a smart bed against polysomnography for sleep apnea detection by Farzad Siyahjani, Kostiantyn Kalenyk, Gary Garcia-Molina, Saeed Babaeizadeh

“…Abstract Sleep-disordered breathing (SDB), including obstructive sleep apnea (OSA) and central sleep apnea (CSA), significantly impairs sleep quality and overall well-being. This study evaluates a novel algorithm, developed and trained by the authors, using ballistocardiography (BCG) data collected from a non-intrusive smart bed platform. …”
Get full text

Survey of video behavior recognition by Huilan LUO, Chanjuan WANG, Fei LU

“…Behavior recognition is developing rapidly,and a number of behavior recognition algorithms based on deep network automatic learning features have been proposed.The deep learning method requires a large number of data to train,and requires higher computer storage and computing power.After a brief review of the current popular behavior recognition method based on deep network,it focused on the traditional behavior recognition methods.Traditional behavior recognition methods usually followed the processes of video feature extraction,modeling of features and classification.Following the basic process,the recognition process was overviewed according to the following steps,feature sampling,feature descriptors,feature processing,descriptor aggregation and vector coding.At the same time,the benchmark data set commonly used for evaluating the algorithm performance was also summarized.…”
Get full text

TF-LIME : Interpretation Method for Time-Series Models Based on Time–Frequency Features by Jiazhan Wang, Ruifeng Zhang, Qiang Li

“…The experiment verified the effectiveness of the TFHS algorithm on Synthetic Dataset 1 and the effectiveness of the TF-LIME algorithm on Synthetic Dataset 2, and then further evaluated the interpretability performance on the MIT-BIH dataset. …”
Get full text

An optimal multi-disease prediction framework using hybrid machine learning techniques by Aditya Gupta, Amritpal Singh

“…Alongside the AdaBoost algorithm, various benchmark machine learning techniques are trained and validated using selected features under a k-fold cross-validation setting. …”
Get full text

Regional Economy Using Hybrid Sequence-to-Sequence-Based Deep Learning Approach by Bo Peng

“…Hybrid sequence to sequence (seq2seq) algorithms of deep learning fed with previous information from past years and run the system to compare the predicted result data with current information to evaluate the method to be certified for the coming years.…”
Get full text

Study on the prediction model of corrosion and scaling in the external cooling water system of ultra-high voltage converter stations phase modulator by GU Xiantao, FAN Peipei, CHEN Xiaochun, GAO Yuxiang, ZHOU Zhongkang, ZHANG Junjie, MA Xiaowei, JI Qiaozhen, WU Yan, XU Yayan, DONG Haosheng, DUAN Zhongxin, YANG Lin, GAO Zhonghui

“…Based on this dataset, a scale prediction model of the circulating cooling water system was trained using backpropagation(BP) neural networks and machine learning algorithms, and the accuracy of the model was evaluated. …”
Get full text

Replicating Current Procedural Terminology code assignment of rhinology operative notes using machine learning by Christopher P. Cheng, Ryan Sicard, Dragan Vujovic, Vikram Vasan, Chris Choi, David K. Lerner, Alfred‐Marc Iloreta

“…Given advancements in machine learning (ML), we evaluated the ability of ML algorithms to use operative notes to classify rhinology procedures by Current Procedural Terminology (CPT®) code. …”
Get full text

Two-Timescale Cross-Layer Design for URLLC Over Parallel Fading Channels With Imperfect CSI by Hongsen Peng, Meixia Tao

“…Based on the small timescale optimization method, we adopt the ternary search algorithm to optimize the pilot length and pilot power through Monte Carlo evaluations in the large timescale. …”
Get full text

A Cascade of Encoder–Decoder with Atrous Convolution and Ensemble Deep Convolutional Neural Networks for Tuberculosis Detection by Noppadol Maneerat, Athasart Narkthewan, Kazuhiko Hamamoto

“…Using the cropped lung images, we trained several pre-trained Deep Convolutional Neural Networks (DCNNs) on the images with hyperparameters optimized by a Bayesian algorithm. …”
Get full text

Enhancing Multi-Disease Prediction with Machine Learning: A Comparative Analysis and Hyperparameter Optimization Approach by Mariam Kili Bechir, Ferhat Atasoy

“…Each algorithm was trained and compared in isolation for each targeted health condition. …”
Get full text

StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification by Muhammad Attique Khan, Muhammad Shahzad Sarfraz, Majed Alhaisoni, Abdulaziz A. Albesher, Shuihua Wang, Imran Ashraf

“…The resultant fusion images are then passed to ResNet101 pre-trained model and trained once again using deep transfer learning. …”
Get full text

Prediction of cardiovascular risk using machine-learning methods. Sex-specific differences by Sara Castel-Feced, Sara Castel-Feced, Sara Castel-Feced, Sara Castel-Feced, Isabel Aguilar-Palacio, Isabel Aguilar-Palacio, Isabel Aguilar-Palacio, Isabel Aguilar-Palacio, Sara Malo, Sara Malo, Sara Malo, Sara Malo, Juan González-García, Lina Maldonado, Lina Maldonado, Lina Maldonado, María José Rabanaque-Hernández, María José Rabanaque-Hernández, María José Rabanaque-Hernández, María José Rabanaque-Hernández

“…These algorithms can also be trained using a growing body of real world data (RWD). …”
Get full text

Concrete crack detection using ridgelet neural network optimized by advanced human evolutionary optimization by Yongqing Lin, Mehdi Ahmadi, Khalid A. Alnowibet, Fawzy A. Bukhari

“…The effectiveness of the RNN/AHEO model was evaluated using various metrics and compared to existing methods. …”
Get full text

A Deep Learning Framework for Chronic Kidney Disease stage classification by Gayathri Hegde M, P Deepa Shenoy, Venugopal KR, Arvind Canchi

“…To evaluate the proposed method, eight DL models — Feedforward Neural Network, Recurrent Neural Network, Deep Neural Network, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Unit (GRU) and Bidirectional GRU were trained on selected features using different FS methods, as well as complete dataset. …”
Get full text

Assessment of soil classification based on cone penetration test data for Kaifeng area using optimized support vector machine by Hanliang Bian, Zhongxun Sun, Jiahan Bian, Zhaowei Qu, Jianwei Zhang, Xiangchun Xu

“…The results revealed that 23 of the algorithms successfully improved the SVM classification accuracy. …”
Get full text