An Efficient CNN Model for COVID-19 Disease Detection Based on X-Ray Image Classification by Aijaz Ahmad Reshi, Furqan Rustam, Arif Mehmood, Abdulaziz Alhossan, Ziyad Alrabiah, Ajaz Ahmad, Hessa Alsuwailem, Gyu Sang Choi

“…To further prove that the proposed model outperforms other models, a comparative analysis has been done with some of the machine learning algorithms. The proposed model has outperformed all the models generally and specifically when the model testing was done using an independent testing set.…”
Get full text

Development of metastasis and survival prediction model of luminal and non-luminal breast cancer with weakly supervised learning based on pathomics by Hui Liu, Linlin Ying, Xing Song, Xueping Xiang, Shumei Wei

“…These features served as the foundational input for developing a machine learning algorithm for metastasis analysis and a Cox regression model for survival analysis. …”
Get full text

5‐Hydroxymethylcytosine Profiles of cfDNA in Urine as Diagnostic, Differential Diagnosis and Prognostic Markers for Multiple Myeloma by Weiwei Xie, Xuehui Li, Hangyu Chen, Jinlin Chu, Lei Zhang, Bo Tang, Wenrong Huang, Linlin Li, Jian Lin, Yujun Dong

“…Then, we applied a machine learning algorithm to develop diagnostic and differential diagnosis model. …”
Get full text

Wearable Regionally Trained AI-Enabled Bruxism-Detection System by Anusha Ishtiaq, Jahanzeb Gul, Zia Mohy Ud Din, Azhar Imran, Khalil El Hindi

“…The augmented data has been trained, validated, and tested on six machine-learning classifiers and three deep-learning models. …”
Get full text

Establishing a GRU-GCN coordination-based prediction model for miRNA-disease associations by Kai-Cheng Chuang, Ping-Sung Cheng, Yu-Hung Tsai, Meng-Hsiun Tsai

“…In recent years, machine learning (ML) and deep learning (DL) techniques are powerful tools to analyze large-scale biological data. …”
Get full text

Assessment of trade-off balance of maize stover use for bioenergy and soil erosion mitigation in Western Kenya by Keiji Jindo, Keiji Jindo, Golaleh Ghaffari, Manisha Lamichhane, Asher Lazarus, Yoshito Sawada, Hans Langeveld

“…A decision-tree machine learning model identified farm characteristics favorable for maize stover use in biogas production.ResultsLarger households were found to consume more energy per capita, while proximity to forests did not significantly influence firewood or charcoal consumption. …”
Get full text

Comparative analysis of the DCNN and HFCNN Based Computerized detection of liver cancer by Sandeep Dwarkanth Pande, Pala Kalyani, S Nagendram, Ala Saleh Alluhaidan, G Harish Babu, Sk Hasane Ahammad, Vivek Kumar Pandey, G Sridevi, Abhinav Kumar, Ebenezer Bonyah

“…Researchers have explored numerous machine learning (ML) techniques and deep learning (DL) approaches aimed at the automated recognition of liver disease by analysing computed tomography (CT) images. …”
Get full text

Association of Premature Ventricular Contraction (PVC) with hematological parameters: a data mining approach by Nafiseh Hosseini, Sara Saffar Soflaei, Pooria Salehi-Sangani, Mahdiyeh Yaghooti-Khorasani, Bahram Shahri, Helia Rezaeifard, Habibollah Esmaily, Gordon A. Ferns, Mohsen Moohebati, Majid Ghayour-Mobarhan

“…The association of hematological factors with PVC was evaluated using different machine learning (ML) algorithms, including logistic regression (LR), C5.0, and boosting decision tree (DT). …”
Get full text

Deep Reinforcemnet Learning for Robust Beamforming in Integrated Sensing, Communication and Power Transmission Systems by Chenfei Xie, Yue Xiu, Songjie Yang, Qilong Miao, Lu Chen, Yong Gao, Zhongpei Zhang

“…Deep reinforcement learning (DRL), a machine learning technique where an agent learns by interacting with its environment, offers a promising approach that can dynamically optimize system performance through adaptive decision-making strategies. …”
Get full text

A Reproducible Method for Donor Site Computed Tomography Measurements in Abdominally Based Autologous Breast Reconstruction by Damini Tandon, MD, Arthur Sletten, MD, PhD, Austin Ha, MD, Gary B. Skolnick, BA, MBA, Paul Commean, BEE, Terence Myckatyn, MD

“…Larger patient cohorts must be leveraged to determine correlations between abdominal CT scan findings and donor site outcomes using machine learning algorithms that generate models for predicting abdominal donor site complications.…”
Get full text

Unified Visual-Aware Representations for Data Analytics by Ladislav Peska, Ivana Sixtova, David Hoksza, David Bernhauer, Jakub Lokoc, Tomas Skopal

“…The visual representations serve for data analytics tasks performed by human users as well as serve for universal data representations used in machine learning models for automated tasks. We show in large study that visual representations of complex data are effective in a number of domains while we also propose a recommender to help with the parameterization of the entire pipeline for certain domains and use cases. …”
Get full text

IL-6-Inducing Peptide Prediction Based on 3D Structure and Graph Neural Network by Ruifen Cao, Qiangsheng Li, Pijing Wei, Yun Ding, Yannan Bin, Chunhou Zheng

“…Most existing methods for predicting IL-6-induced peptides use traditional machine learning methods, whose feature selection is based on prior knowledge. …”
Get full text

Local Binary and Multiclass SVMs Trained on a Quantum Annealer by Enrico Zardini, Amer Delilbasic, Enrico Blanzieri, Gabriele Cavallaro, Davide Pastorello

“…Support vector machines (SVMs) are widely used machine learning models, with formulations for both classification and regression tasks. …”
Get full text

The potential for fuel reduction to reduce wildfire intensity in a warming California by Patrick T Brown, Scott J Strenfel, Richard B Bagley, Craig B Clements

“…Here, we quantify the potential for fuel reduction to reduce wildfire intensity using empirical relationships derived from historical observations with a novel combination of spatiotemporal resolution (0.375 km, instantaneous) and extent (48 million acres, 9 years). We use machine learning to quantify relationships between sixteen environmental conditions (including ten fuel characteristics and four temperature-affected aridity characteristics) and satellite-observed fire radiative power. …”
Get full text

Anthropometric Landmark Detection Network via Geodesic Heatmap on 3D Human Scan by Min Hee Cha, Jae Hyeon Park, Ji Sun Byun, Sangyeon Ahn, Gyoomin Lee, Seung Hyun Yoon, Sung In Cho

“…With advancement in computer vision and machine learning, researchers have increasingly focused on developing automated anthropometric data extraction technique. …”
Get full text

Impacts of IOD and ENSO on the phytoplankton’s vertical variability in the Northern Indian Ocean by Qiwei Hu, Xiaoyan Chen, Xianqiang He, Yan Bai, Tingchen Jiang, Yu Huan, Zhanlin Liang

“…Using the three-dimensional Chlorophyll a concentration dataset generated by a machine learning model, this study examines IOD- and ENSO-linked vertical phytoplankton anomalies over the entire euphotic layer (0–100 m) in the NIO during 2000–2019. …”
Get full text

Prediction of the Influential Factors on Eating Behaviors: A Hybrid Model of Structural Equation Modelling-Artificial Neural Networks by Maryam M. Kheirollahpour, Mahmoud M. Danaee, Amir Faisal A. F. Merican, Asma Ahmad A. A. Shariff

“…Thus, a hybrid approach could be suggested as a significant methodological contribution from a machine learning standpoint, and it can be implemented as software to predict models with the highest accuracy.…”
Get full text

SpikeDroidDB: AN INFORMATION SYSTEM FOR ANNOTATION OF MORPHOMETRIC CHARACTERISTICS OF WHEAT SPIKE by M. A. Genaev, E. G. Komyshev, Fu Hao, V. S. Koval, N. P. Goncharov, D. A. Afonnikov

“…The effectiveness of ears’ phenotyping can be improved by the introduction of an automated image processing technology, storage of information in databases, use of machine learning algorithms to analyze this information. …”
Get full text

APT Adversarial Defence Mechanism for Industrial IoT Enabled Cyber-Physical System by Safdar Hussain Javed, Maaz Bin Ahmad, Muhammad Asif, Waseem Akram, Khalid Mahmood, Ashok Kumar Das, Sachin Shetty

“…The objective of Advanced Persistent Threat (APT) attacks is to exploit Cyber-Physical Systems (CPSs) in combination with the Industrial Internet of Things (I-IoT) by using fast attack methods. Machine learning (ML) techniques have shown potential in identifying APT attacks in autonomous and malware detection systems. …”
Get full text

Chronic lung lesions in COVID-19 survivors: predictive clinical model by Paulo A Lotufo, Juliana C Ferreira, Eloisa Bonfa, Anna S Levin, Rodrigo Caruso Chate, Marta Imamura, Esper G Kallas, Roger Chammas, Thais Mauad, Izabel Marcilio, Nelson Gouveia, Ricardo Nitrini, José Eduardo Krieger, Marcio Valente Yamada Sawamura, Michelle Louvaes Garcia, Cristiano Gomes, Guilherme Fonseca, Jorge Hallak, Luis Yu, Marcio Mancini, Maria Elizabeth Rossi, Thiago Avelino-Silva, Edivaldo M Utiyama, Aluisio C Segurado, Beatriz Perondi, Anna Miethke-Morais, Amanda C Montal, Leila Harima, Marjorie F Silva, Marcelo C Rocha, Maria Amélia de Jesus, Carolina Carmo, Clarice Tanaka, Julio F M Marchini, Thaís Guimarães, Ester Sabino, Carlos Roberto Ribeiro Carvalho, Celina Almeida Lamas, Diego Armando Cardona Cardenas, Daniel Mario Lima, Paula Gobi Scudeller, João Marcos Salge, Cesar Higa Nomura, Marco Antonio Gutierrez, Adriana L Araújo, Bruno F Guedes, Carolina S Lázari, Cassiano C Antonio, Claudia C Leite, Emmanuel A Burdmann, Euripedes C Miguel, Fabio R Pinna, Fabiane Y O Kawano, Geraldo F Busatto, Giovanni G Cerri, Heraldo P Souza, Izabel C Rios, Larissa S Oliveira, Linamara R Batisttella, Luiz Henrique M Castro, Marcello M C Magri, Maria Cassia J M Corrêa, Maria Cristina P B Francisco, Maura S Oliveira, Orestes V Forlenza, Ricardo F Bento, Rodolfo F Damiano, Rossana P Francisco, Solange R G Fusco, Tarcisio E P Barros-Filho, Wilson J Filho

“…Patients with abnormalities in at least one of these parameters underwent chest CT. mMRC scale, SpO2, FVC and CXR findings were used to build a machine learning model for lung lesion detection on CT.Setting A tertiary hospital in Sao Paulo, Brazil.Participants 749 eligible RT-PCR-confirmed SARS-CoV-2-infected patients aged ≥18 years.Primary outcome measure A predictive clinical model for lung lesion detection on chest CT.Results There were 470 patients (63%) that had at least one sign of pulmonary involvement and were eligible for CT. …”
Get full text