Clinical, genetic, and sociodemographic predictors of symptom severity after internet-delivered cognitive behavioural therapy for depression and anxiety by Olly Kravchenko, Julia Bäckman, David Mataix-Cols, James J. Crowley, Matthew Halvorsen, Patrick F. Sullivan, John Wallert, Christian Rück

“…Employing machine learning algorithms capable of capturing complex non-linear associations and interactions is a viable next step to improve prediction of post-ICBT symptom severity. …”
Get full text

A Novel Dual-Branch Global and Local Feature Extraction Network for SAR and Optical Image Registration by Xuanran Zhao, Yan Wu, Xin Hu, Zhikang Li, Ming Li

“…However, the inherent differences between the two modalities pose a challenge to the existing deep-learning algorithms that only depend on local features. To address this problem, we propose a global and local feature extraction network (GLFE-Net) for SAR and optical image registration. …”
Get full text

A Low Power Memory-Integrated Hardware BNN-MLP Model on an FPGA for Current Signals in a Biosensor by Geon-Hoe Kim, Dong-Gyun Kim, Sung-Jae Lee, Jong-Han Kim, Da-Yeong An, Hyejin Kim, Young-Gun Pu, Heejeong Jasmine Lee, Jun-Eun Park, Kang-Yoon Lee

“…This paper presents a method for processing and digitizing the current signal information output from biosensors and a hardware Artificial Intelligence (AI) model design that classifies data using low-power and compact AI algorithms to minimize the high-power consumption and on chip area of the Convolutional Neural Network (CNN) models used in biosensors. …”
Get full text

Railway Tracks Extraction from High Resolution Unmanned Aerial Vehicle Images Using Improved NL-LinkNet Network by Jing Wang, Xiwei Fan, Yunlong Zhang, Xuefei Zhang, Zhijie Zhang, Wenyu Nie, Yuanmeng Qi, Nan Zhang

“…Traditional computer vision algorithms struggle with the complexities of high-precision track extraction due to challenges such as diverse track shapes, varying angles, and complex background information in UAV images. …”
Get full text

The prevalence of resistance-associated mutations to protease and reverse transcriptase inhibitors in treatment-naïve (HIV1)-infected individuals in Casablanca, Morocco by Khadija Bakhouch, Ahd Oulad-Lahcen, Rajae Bensghir, Mohamed Blaghen, Kamal Marhoum Elfilali, Sayeh Ezzikouri, Omar Abidi, Mohamed Hassar, Lahcen Wakrim

“…National Agency for AIDS Research (ANRS) and Stanford HIV database algorithms were used for interpretation of resistance data. …”
Get full text

Coupling Remote Sensing With a Process Model for the Simulation of Rangeland Carbon Dynamics by Yushu Xia, Jonathan Sanderman, Jennifer D. Watts, Megan B. Machmuller, Andrew L. Mullen, Charlotte Rivard, Arthur Endsley, Haydee Hernandez, John Kimball, Stephanie A. Ewing, Marcy Litvak, Tomer Duman, Praveena Krishnan, Tilden Meyers, Nathaniel A. Brunsell, Binayak Mohanty, Heping Liu, Zhongming Gao, Jiquan Chen, Michael Abraha, Russell L. Scott, Gerald N. Flerchinger, Patrick E. Clark, Paul C. Stoy, Anam M. Khan, E. N. Jack Brookshire, Quan Zhang, David R. Cook, Thomas Thienelt, Bhaskar Mitra, Marguerite Mauritz‐Tozer, Craig E. Tweedie, Margaret S. Torn, Dave Billesbach

“…We developed the Rangeland Carbon Tracking and Management (RCTM) system to track long‐term changes in SOC and ecosystem C fluxes by leveraging remote sensing inputs and environmental variable data sets with algorithms representing terrestrial C‐cycle processes. …”
Get full text

Identification and quantification of transposable element transcripts using Long-Read RNA-seq in Drosophila germline tissues by Rebollo, Rita, Gerenton, Pierre, Cumunel, Eric, Mary, Arnaud, Sabot, François, Burlet, Nelly, Gillet, Benjamin, Hughes, Sandrine, S. Oliveira, Daniel, Goubert, Clément, Fablet, Marie, Vieira, Cristina, Lacroix, Vincent

“…Methods to identify and quantify TE transcription have mostly relied on short RNA-seq reads to estimate TE expression at the family level while using specific algorithms to discriminate copy-specific transcription. …”
Get full text

Large-area urban TomoSAR method with limited a priori knowledge and a complex deep learning model by Haoxuan Duan, Yuzhou Liu, Hong Zhang, Peifeng Ma, Zhongqi Shi, Zihuan Guo, Yixian Tang, Fan Wu, Chao Wang

“…Additionally, the computational inefficiency of existing algorithms significantly hinders the large-scale practical deployment of TomoSAR. …”
Get full text

Mapping the global risk of chikungunya virus endemicity and autochthonous transmission following importation by Yu-Feng Yang, Yun-Bo Qiu, Qiang Xu, Rui-Cheng Gao, Tian Tang, Yao Tian, Yan-He Wang, Sheng-Hong Lin, Yun-Dong Shi, Long-Tao Chen, Yan Zhang, Jun Ma, Chen-Long Lv, Guo-Lin Wang, Hai-Feng Pan, Wei Liu, Li-Qun Fang

“…Three machine learning algorithms were utilized to analyze the ecological factors associated with CHIKV occurrences in regions characterized by endemic or autochthonous transmission following importation. …”
Get full text

Using Machine Learning to Assess the Effects of Biochar-Based Fertilizers on Crop Production and N₂O Emissions in China by Yuan Zeng, Sujuan Chen, Yunpeng Li, Li Xiong, Cheng Liu, Muhammad Azeem, Xiaoting Jie, Mei Chen, Longjiang Zhang, Jianfei Sun

“…This study uses a global dataset of BBF field experiments to build predictive models with three machine learning algorithms for crop yields and N₂O emissions, and to assess BBFs’ potential to increase yields and mitigate emissions in China’s major crops. …”
Get full text

Integrated bioinformatics analysis to develop diagnostic models for malignant transformation of chronic proliferative diseases by Hua Liu, Sheng Lin, Pei-Xuan Chen, Juan Min, Xia-Yang Liu, Ting Guan, Chao-Ying Yang, Xiao-Juan Xiao, De-Hui Xiong, Sheng-Jie Sun, Ling Nie, Han Gong, Xu-Sheng Wu, Xiao-Feng He, Jing Liu

“…Integrated public datasets of PV and AML were analyzed to identify differentially expressed genes (DEGs) and construct a weighted correlation network. Machine-learning algorithms screen genes for potential biomarkers, leading to the development of diagnostic models. …”
Get full text

Machine learning and response surface methodology forecasting comparison for improved spray dry scrubber performance with brine sludge-derived sorbent by B.J. Chepkonga, L. Koech, R.S. Makomere, H.L. Rutto

“…The response surface methodology (RSM) model also proved to be a reliable forecasting tool, indicating its potential as a practical alternative to complex algorithmic computations in scenarios with limited raw data.…”
Get full text

Quantitative Analysis of Lithium in Natural Brines from the Lithium Triangle by Laser-Induced Breakdown Spectroscopy by Juan Molina M., Carisa Sarchi, Alvaro Y. Tesio, César Costa-Vera, Diego M. Díaz Pace

“…Broadband emission spectra (180–900 nm) were recorded and spectrally analyzed by specially designed computational algorithms. The laser-induced plasmas were characterized by calculating the electron density and the temperature. …”
Get full text

IoT-driven real-time weather measurement and forecasting mobile application with machine learning integration by Jul Jalal Al-Mamur Sayor, Nishat Tasnim Shishir, Bitta Boibhov Barmon, Sumon Ahemed, Md. Moshiur Rahman

“…APIs (Application Programming Interface) enable efficient data input and retrieval, guaranteeing smooth connection and integration between the sensors and the forecasting algorithms. Moreover, we analyze forecasts from Google and systematically compare them with our localized predictions to highlight the advantages of site-specific deployment for achieving superior localized outcomes. …”
Get full text

Prediction of obesity levels based on physical activity and eating habits with a machine learning model integrated with explainable artificial intelligence by Yasin Görmez, Fatma Hilal Yagin, Burak Yagin, Yalin Aygun, Hulusi Boke, Georgian Badicu, Matheus Santos De Sousa Fernandes, Abedalrhman Alkhateeb, Mahmood Basil A. Al-Rawi, Mohammadreza Aghaei, Mohammadreza Aghaei

“…In terms of interpretability, LIME showed superior in fidelity, whereas SHAP showed improved sparsity and consistency across models, facilitating a comprehensive understanding of trait importance.ConclusionThis research demonstrates that ML algorithms, when integrated with XAI technologies, can accurately predict obesity levels and explain important contributing risk factors. …”
Get full text

The Impact of Integrated Project-Based Learning and Flipped Classroom on Students’ Computational Thinking Skills: Embedded Mixed Methods by Muh Fitrah, Anastasia Sofroniou, Caly Setiawan, Widihastuti Widihastuti, Novi Yarmanetti, Melinda Puspita Sari Jaya, Jontas Gayuh Panuntun, Arfaton Arfaton, Septrisno Beteno, Ika Susianti

“…Although there was an improvement in algorithmic thinking skills, some students still faced difficulties in developing systematic solutions. …”
Get full text

On-Demand Gait-Synchronous Electrical Cueing in Parkinson's Disease Using Machine Learning and Edge Computing: A Pilot Study by Ardit Dvorani, Constantin Wiesener, Christina Salchow-Hommen, Magdalena Jochner, Lotta Spieker, Matej Skrobot, Hanno Voigt, Andrea Kuhn, Nikolaus Wenger, Thomas Schauer

“…<italic>Methods:</italic> We present a new technical solution, that runs detection and cueing algorithms directly on the sensing and cueing devices, bypassing the smartphone. …”
Get full text

Multi-atlas multi-modality morphometry analysis of the South Texas Alzheimer’s Disease Research Center postmortem repository by Nicolas Honnorat, Mariam Mojtabai, Karl Li, Jinqi Li, David Michael Martinez, Tanweer Rashid, Morgan Smith, Margaret E Flanagan, Elyas Fadaee, Morgan Fox Torres, Mallory Keating, Kevin Bieniek, Sudha Seshadri, Mohamad Habes

“…In general, our results establish that a combination of structural MRI sequences can provide enough informa- tion for state-of-the-art Deep Learning algorithms to almost perfectly separate brain tissues from a formalin buffered solution. …”
Get full text

A new online dynamic nomogram based on the inflammation burden index to predict cardiac injury after antitumor therapy in lung cancer patients by Yumin Wang, Chunyan Huan, Huijuan Pu, Guodong Wang, Yan Liu, Xiuli Zhang, Chengyang Li, Jie Liu, Wanling Wu, Defeng Pan

“…Statistical analysis using SPSS 22.0 and R 4.4.1, including machine learning algorithms and multivariate logistic analysis, identified independent predictors of cardiac injury. …”
Get full text

What are new opportunities for clinical practice the VERIFY study opens and which values for native diabetes patients? Joint conclusion on the advisory board results. November 6, 2... by Marina V. Shestakova, Mikhail B. Antsiferov, Alexander S. Ametov, Gagik R. Galstyan, Tatiana Y. Demidova, Alexey V. Zilov, Tatiana N. Markova, Nina A. Petunina, Natalya A. Chernikova, Minara S. Shamkhalova

“…However, due to the fact that the clinical benefits of early combination therapy were not demonstrated in randomized clinical trials, this approach, despite the theoretical background, was not recommended for widespread use in international guidelines for the treatment diabetes patients. Russian algorithms on the treatment diabetes patients recommend combined glucose lowering therapy at the start of treatment at a HbA1c level of 1% higher than the target. …”
Get full text