Smart Management of Energy Losses in Distribution Networks Using Deep Neural Networks by Ihor Blinov, Virginijus Radziukynas, Pavlo Shymaniuk, Artur Dyczko, Kinga Stecuła, Viktoriia Sychova, Volodymyr Miroshnyk, Roman Dychkovskyi

“…Given the presence of anomalies and missing values in the operational data, a two-stage preprocessing algorithm incorporating DBSCAN clustering was applied for data cleansing and imputation. …”
Get full text

Body mass index as the main predictor for length of stay in COVID-19 patients with mild and moderate symptoms: a cross-sectional study in COVID-19 emergency hospital in Indonesia by Siti Rahayu Nadhiroh, Anisa Lailatul Fitria, Armedy Ronny Hasugian, Erwin Astha Triyono, Nono Tri Nugroho, Alfadhila Khairil Sinatrya, Hazreen B Abdul Majid

“…The Chi-square automatic interaction detection (CHAID) algorithm was employed for model building. Results: Most participants were overweight (34.6%) and obese (17.2%). …”
Get full text

AAMS-YOLO: enhanced farmland parcel detection for high-resolution remote sensing images by Binyao Wang, Ya’nan Zhou, Weiwei Zhu, Li Feng, Jinke He, Tianjun Wu, Jiancheng Luo, Xin Zhang

“…During feature enhancement, to effectively detect targets of different scales, the Attentional Scale Sequence Fusion with P2 network (ASFP2Net) integrates the Triple Feature Encoder (TFE) module and Scale Sequence Feature Fusion (SSFF) module. In the prediction stage, a Multi-Scale Attention Head (MSAHead) enhances adaptability through multi-scale attention mechanisms. …”
Get full text

Resampling-driven machine learning models for enhanced high streamflow forecasting by Nureehan Salaeh, Sirimon Pinthong, Warit Wipulanusat, Uruya Weesakul, Jakkarin Weekaew, Quoc Bao Pham, Pakorn Ditthakit

“…These results present a promising framework for high streamflow prediction that can be adapted and applied to other river basins.…”
Get full text

Use of machine learning in osteoarthritis research: a systematic literature review by Francis Berenbaum, Jérémie Sellam, David Klatzmann, Atul J Butte, Karine Louati, Encarnita Mariotti-Ferrandiz, Marie Binvignat, Valentina Pedoia

“…Twelve articles were related to diagnosis, 7 to prediction, 4 to phenotyping, 12 to severity and 11 to progression. …”
Get full text

Evaluating Critical Success Factors in AI-Driven Drug Discovery Using AHP: A Strategic Framework for Optimization by Amir Mohamed Talib, Areen Metib Al-Hgaish, Rodziah Binti Atan, Abdulaziz Alshammari, Fahad Omar Alomary, Razali Yaakob, Abdulaziz Alsahli, Mohd Hafeez Osman

“…This comprehensive evaluation is a valuable resource for researchers and industry professionals, facilitating the strategic adoption of AI and bridging the gap between computational predictions and real-world therapeutic outcomes.…”
Get full text

Method for Knowledge Transfer via Multi-Task Semi-Supervised Self-Paced by Yao Zhao, Hongying Liu, Huaxian Pan, Zhen Song, Chunting Liu, Anni Wei, Baoshuang Zhang, Wei Lu

“…Experimental results on several benchmark datasets show that our method achieves a performance gain of 3%-15% in classification accuracy compared to baseline algorithms, along with significant advantages in convergence speed.…”
Get full text

Reconsidering CPR protocols: Exploring hypernatremia's role in ventricular tachycardia from a case report by Arthur Gavotto, Jean-Yves Le Guennec, Cyril Amouroux, Pascal Champeroux, Angelo Polito, Jérôme Thireau, Alain Lacampagne, Gilles Cambonie

“…Conclusion: In silico modelling can help to predict arrhythmia risk and to select the best strategies. …”
Get full text

Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability by Danish Raza, Hong Shu, Muhsan Ehsan, Hong Fan, Kamal Abdelrahman, Hasnat Aslam, Abdul Quddoos, Rana Waqar Aslam, Majid Nazeer, Mohammed S. Fnais, Azeem Sardar

“…First, by incorporating more than three decades of satellite data (1990–2022) and different Landsat missions with machine learning algorithms, high-confidence classes were defined for different land features, including cropland. …”
Get full text

Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies by Rahul Kumar, Ethan Waisberg, Joshua Ong, Phani Paladugu, Dylan Amiri, Jeremy Saintyl, Jahnavi Yelamanchi, Robert Nahouraii, Ram Jagadeesan, Alireza Tavakkoli

“…When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and inflammation. …”
Get full text

Automatic maxillary sinus segmentation and age estimation model for the northwestern Chinese Han population by Yu-Xin Guo, Jun-Long Lan, Wen-Qing Bu, Yu Tang, Di Wu, Hui Yang, Jia-Chen Ren, Yu-Xuan Song, Hong-Ying Yue, Yu-Cheng Guo, Hao-Tian Meng

“…Age estimation models using multiple linear regression and random forest algorithms were built based on these variables. Results The automatic segmentation model achieved high accuracy, which yielded a Dice similarity coefficient (DSC) of 0.873, an Intersection over Union (IoU) of 0.7753, a Hausdorff Distance 95% (HD95) of 9.8337, and an Average Surface Distance (ASD) of 2.4507. …”
Get full text

Combined influence of crushed brick powder and recycled concrete aggregate on the mechanical, durability and microstructural properties of eco-concrete: An experimental and machine... by Md. Habibur Rahman Sobuz, Mahmudur Hossain Khan, Md. Rakibul Islam, Md. Kawsarul Islam Kabbo, Abdullah Alzlfawi, M Jameel, Md. Munir Hayet Khan

“…Additionally, the study evaluates machine learning algorithms such as extreme gradient boosting (XG Boost), random forest (RF), and bagging model (BAG) for predicting the mechanical strength of concrete specimens. …”
Get full text

Comparative Analysis of Computed Tomography and Laparoscopy Data in Preoperative Staging of Gastric Cancer by N. K. Silanteva, T. A. Аgababyan, A. A. Kholeva, V. Yu. Skoropad, Z. N. Shavladze, S. A. Ivanov, L. P. Zhavoronkov

“…The combined use of CT and DL is a current algorithm for examining patients with gastric cancer. …”
Get full text

Climatic suitability and potential distribution of earleaf acacia and its candidate biological control agent Trichilogaster sp by Sara S. MacDonald, Emily J. Le Falchier, Lindsay P. Campbell, Ryan Zonneveld, Carey R. Minteer

“…Both models exhibit high predictive accuracy, with AUC values above 0.9. This study emphasizes the need for continued monitoring and management of ELA and evaluates areas in Florida predicted to have suitable climatic conditions for Trichilogaster sp. nov. …”
Get full text

Development of Anthro-Fitness Model for Evaluating Firefighter Recruits’ Performance Readiness Using Machine Learning by Mohamed Borhanudin Mohd Yusof, Musa Rabiu Muazu, Nazarudin Mohamad Nizam, Abdul Majeed Anwar P. P., Raj Naresh Bhaskar, Razmaan Mohd Azraai Mohd

“…A k-means clustering algorithm was utilized to group the performance levels of the firefighters whilst a quadratic discriminant analysis model was employed to predict the grouping of firefighters based on these parameters. …”
Get full text

Permanent terrestrial laser scanning for near-continuous environmental observations: Systems, methods, challenges and applications by Roderik Lindenbergh, Katharina Anders, Mariana Campos, Daniel Czerwonka-Schröder, Bernhard Höfle, Mieke Kuschnerus, Eetu Puttonen, Rainer Prinz, Martin Rutzinger, Annelies Voordendag, Sander Vos

“…Many topographic scenes exhibit complex dynamic behavior that is difficult to map, quantify, predict and understand. A terrestrial laser scanner fixed on a permanent position can be used to monitor such scenes in an automated way with centimeter to decimeter quality at ranges of up to several kilometers. …”
Get full text

De novo KCNK4 variant caused epilepsy with febrile seizures plus, neurodevelopmental abnormalities, and hypertrichosis by Hong-Jun Yan, Wen-Hui Liu, Min-Xing Xu, Peng-Yu Wang, Yu-Jie Gu, Hua Li, Jing Guo, Sheng Luo

“…The identified variant was absent in normal populations, indicated to alter hydrogen bonds with surrounding residues by various protein modeling, predicted to be damaging for protein function by twenty algorithms, located in residues of high conservation across species, and classified as pathogenic by the ACMG guidelines. …”
Get full text

Visualization of Moisture Distribution in Stacked Tea Leaves on Process Flow Line Using Hyperspectral Imaging by Yuying Zhang, Binhui Liao, Mostafa Gouda, Xuelun Luo, Xinbei Song, Yihang Guo, Yingjie Qi, Hui Zeng, Chuangchuang Zhou, Yujie Wang, Jingfei Zhang, Xiaoli Li

“…In this study, we utilized hyperspectral imaging (HSI) technology combined with machine learning algorithms to evaluate the moisture content and its distribution in the stacked tea leaves in West Lake Longjing and Tencha green tea products during the processing flow line. …”
Get full text

Determining time since deposition of latent fingerprints on forensic adhesive tape using ultrafast DESI-MS and machine learning by Nora Rajs, Yinon Harush-Brosh, Ron Raisch, Ravit Yakobi Arancibia, Amani Zoabi, Guy Nevet Golan, Moshe Shpitzen, Sarena Wiesner, Michal Levin-Elad, Tommy Kaplan, Katherine Margulis

“…Data analysis using the XGBoost and SMOTE algorithms achieved a correlation of 0.54 (p-value < 1e−5) between TSD prediction and true TSD, achieving 83.3% accuracy in distinguishing between 0-4 days and 10–15 days old prints. …”
Get full text

An optimization-inspired intrusion detection model for software-defined networking by Hui Xu, Longtan Bai, Wei Huang

“…This paper proposes an enhanced spider wasp optimizer (ESWO) algorithm for feature dimensionality reduction of intrusion detection datasets and constructs a new intrusion detection model (IDM), namely ESWO-IDM, for SDN. …”
Get full text