Enhancing healthcare with AI: Sustainable AI and IoT-Powered ecosystem for patient aid and interpretability analysis using SHAP by Biplov Paneru, Bishwash Paneru, Sanjog Chhetri Sapkota, Ramhari Poudyal

“…Finally, the Shapley Additive Explanations (SHAP) is used here for finding out the most influential parameters, and Explainable AI (XAI) is utilized with the help of SHAP values for enhanced information on affecting parameters. …”
Get full text

Influence of Loading Frequency on Fatigue of Construction Materials by V. V. Mylnikov

“…Behavior dynamics for real machine parts and structures made of these alloys under operating conditions has been indicated in the paper.…”
Get full text

Prediction of Neoadjuvant Chemoradiotherapy Sensitivity in Patients With Esophageal Squamous Cell Carcinoma Using CT-Based Radiomics Combined With Clinical Features by Xindi Li, Jigang Dong, Baosheng Li, Ouyang Aimei, Yahong Sun, Xia Wu, Wenjuan Liu, Ruobing Li, Zhongyuan Li, Yu Yang

“…Objective: This study aimed to establish a predictive model, based on computed tomography (CT) radiomics features and clinical parameters, to predict sensitivity to nCRT in patients with ESCC pre-treatment. …”
Get full text

Utility of global longitudinal strain as an early marker of subclinical left ventricular dysfunction in patients with valvular heart disease by Susheel Kumar Malani, Vijay Sharma, Sridevi Chigullapalli, Aviral Ratan Shrivastav, Ananya Gupta

“…Participants underwent echocardiographic evaluation using 2D and speckle-tracking echocardiography to assess GLS, LV volumes, ejection fraction, and other myocardial deformation parameters using Vivid™ E95 Ultra Edition ECHO machine. …”
Get full text

N-[(1RS)-camphane-2-ylidene]aniline: A novel efficient liquid UV absorber for 3D printing by N. V. Sidorenko, M. A. Vaniev, Iu. M. Mkrtchyan, N. A. Salykin, A. A. Vernigora, I. A. Novakov

“…Polymerization process parameters were determined using а Netzsch DSC 204 F1 Phoenix differential scanning calorimeter equipped with an OmniCure S2000 UV irradiation attachment (400–500 nm filter). …”
Get full text

A concept for H2-Diesel engines: CFD-driven dual spray optimization with energy/exergy analysis for enhanced performance and sustainable combustion by Kourosh Ghadamkheir, Mohammad Moghiman, Mohammad Hatami

“…A detailed model was developed to assess the influence of key injection parameters on energy and exergy efficiencies, combustion characteristics, and output emissions. …”
Get full text

Development of an end-to-end automated production concept for extrusion-based additive manufacturing of personalized medical scaffolds by Kai Janning, Sven König, Laura Herbst, Bastian Nießing, Robert H. Schmitt, Robert H. Schmitt

Get full text

Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

“…Second, relevant characteristic parameters were chosen from geological conditions, production characteristics, and fracturing techniques to perform clustering analysis on fracturing intervals in the data sample. …”
Get full text

Assessment of addiction behavior and spermatogenesis in glial cell line-derived neurotrophic factor-treated cannabis-addicted rats: An experimental study by Rozhina Laleh, Mitra Heydari Nasrabadi, Parvin Khodarahmi, Jamshid Soltani

“…Conclusion: The findings of this experiment suggest that exogenous GDNF could be a potential therapeutic agent for cannabis addiction and sperm parameters. …”
Get full text

Automatic Precision Planting Mechanism of Garlic Seeder by Guilin Chen, Yifan Yao, Lili Yi, Xiang Yin, Juan Du, Jun Chong

“…A kinematic model of the insertion planting process was established, with key parameters meticulously described and analyzed, providing theoretical support for determining optimal insertion parameters. …”
Get full text

A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training by Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu

“…Abstract Deep learning is one of the most popular machine learning methods, and has been used in many applications. …”
Get full text

Decomposition of Technological Processes for Evaluating the Performance of Production Line for Pre Sowing Treatment of Seeds by E. I. Kubeyev, B. S. Antropov

“…(Conclusions) The authors have studied main parameters and operating modes of a seed pelleting installation. …”
Get full text

Influence of agricultural machinery on the potential realization of winter hard wheat yield by A. G. Galayan, S. N. Medvedko, A. V. Bondarev, V. Y. Chundyshko

Get full text

Electrophysiological-based automatic subgroups diagnosis of patients with chronic dysimmune polyneuropathies by Sara Ballanti, Piergiuseppe Liuzzi, Paolo Luca Mattiolo, Maenia Scarpino, Sabrina Matà, Bahia Hakiki, Francesca Cecchi, Calogero Maria Oddo, Andrea Mannini, Antonello Grippo

“…Conclusions The study is the first to apply computational methods to identify electrophysiological parameters most frequently altered in different forms of polyneuropathy, to support clinical diagnosis and decision-making.…”
Get full text

Classification and Recognition of Soybean Quality Based on Hyperspectral Imaging and Random Forest Methods by Man Chen, Zhichang Chang, Chengqian Jin, Gong Cheng, Shiguo Wang, Youliang Ni

“…It also offers a reference for the development of future machine-harvested soybean breakage and impurity detection systems.…”
Get full text

Modeling for the Prediction and Evaluation of the Crimp Percentage of Plain Woven Fabric Based on Yarn Count and Thread Density by Kura Alemayehu Beyene, Chirato Godana Korra

“…Crimp percentage is impacted by fiber, yarn, fabric structural parameters and machine setting parameters. This makes the crimp percentage difficult to control and study, but this developed model can be easily used by manufacturers or researchers for controlling and studying purposes. …”
Get full text

Optimization of the fermentation process for fructosyltransferase production by Aspergillus niger FS054 by Yingzi Wu, Yuewen Zhang, Xiaoyu Zhong, Huiling Xia, Mingyang Zhou, Wenjin He, Yi Zheng

“…Abstract This study systematically optimized the fermentation process for fructosyltransferase (FTase) production by Aspergillus niger FS054, integrating traditional experimental designs with machine learning approaches. Single–factor experiments initially identified critical medium components (carbon source, nitrogen sources, phosphate, and metal ions) and cultivation parameters (pH, liquid volume, inoculum size, temperature, and shaking speed). …”
Get full text

Skin cancer detection using dermoscopic images with convolutional neural network by Khadija Nawaz, Atika Zanib, Iqra Shabir, Jianqiang Li, Yu Wang, Tariq Mahmood, Amjad Rehman

“…Early detection and treatment are crucial for a cure. Machine learning studies have focused on classifying melanoma tumors, but these methods are cumbersome and fail to extract deeper features. …”
Get full text

Data driven prediction of fragment velocity distribution under explosive loading conditions by Donghwan Noh, Piemaan Fazily, Songwon Seo, Jaekun Lee, Seungjae Seo, Hoon Huh, Jeong Whan Yoon

“…This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition. …”
Get full text

Identification of digital twins to guide interpretable AI for diagnosis and prognosis in heart failure by Feng Gu, Andrew J. Meyer, Filip Ježek, Shuangdi Zhang, Tonimarie Catalan, Alexandria Miller, Noah A. Schenk, Victoria E. Sturgess, Domingo Uceda, Rui Li, Emily Wittrup, Xinwei Hua, Brian E. Carlson, Yi-Da Tang, Farhan Raza, Kayvan Najarian, Scott L. Hummel, Daniel A. Beard

“…Unsupervised machine learning applied to digital twin-derived features identified interpretable phenogroups and mechanistic drivers of cardiovascular death risk. …”
Get full text