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

Investigation of Subband Electron Temperatures of Quantum Cascade Lasers by Chen Peng, Yuankun Sun, Liguo Zhu, Tao Chen, Gang Chen, Anping Yu, Sencheng Zhong, Pingwei Zhou, Zhaohui Zhai, Zeren Li

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

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

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

Investigating the Stroke- and Aging-Related Changes in Intermuscular Coupling by Refined Composed Multiscale Fuzzy Entropy by Hairong Yu, Yuanyu Wu, Rong Song

Get full text

Integrating Experimental Analysis and Gradient Boosting for the Durability Assessment of Lime-Based Mortar in Acidic Environment by Ali Taheri, Nima Azimi, Daniel V. Oliveira, Joaquim Tinoco, Paulo B. Lourenço

“…In the modeling phase, the extreme gradient boosting (XGBoost) algorithm was deployed to predict the mechanical properties of the lime-based mortar by 1000, 3000, and 5000 h of exposure. …”
Get full text

Spatial and temporal heterogeneity in high-grade serous ovarian cancer: a phylogenetic analysis. by Roland F Schwarz, Charlotte K Y Ng, Susanna L Cooke, Scott Newman, Jillian Temple, Anna M Piskorz, Davina Gale, Karen Sayal, Muhammed Murtaza, Peter J Baldwin, Nitzan Rosenfeld, Helena M Earl, Evis Sala, Mercedes Jimenez-Linan, Christine A Parkinson, Florian Markowetz, James D Brenton

“…<h4>Conclusions</h4>This study demonstrates that quantitative measures of intra-tumour heterogeneity may have predictive value for survival after chemotherapy treatment in HGSOC. …”
Get full text

Flow cytometry for screening and prioritisation of urine samples: a retrospective comparison with culture by Vicky Sender, John Kerr White, Ludvig Bolinder, Karin Amilon, Mirja Hägg, Karin Haij Bhattarai, Niklas K. Björkström, Baharak Saeedi

“…Results Based on our data, we propose an algorithm using bacterial count from UFC to guide urine culture decisions. …”
Get full text

The role of artificial intelligence in managing hospitalized patients with mental illness: a scoping review by Md Samiun, Moustaq Karim Khan Rony, Sumaiya Yeasmin, Mia Md Tofayel Gonee Manik, Anupom Debnath, Mustakim Bin Aziz, Afia Fairooz Tasnim, Sadia Islam Nilima

“…Despite these advancements, challenges were noted, such as algorithmic biases due to non-diverse training data, privacy and security risks for sensitive patient information, and clinician resistance stemming from concerns about autonomy and ethical implications of AI-supported clinical decisions. …”
Get full text

MODERN APPROACHES TO CLINICAL AND LABORATORY DIAGNOSTICS OF RHEUMATOID ARTHRITIS EARLY ONSET by D. G. Rekalov, S. Y. Dotsenko, A. V. Kylinich

“…The data on the sensitivity and specificity of the diagnostic classification and clinical criteria of eRA and an algorithm for the identification of the disease were presented. …”
Get full text

Electronic nose and machine learning for modern meat inspection by Ivan Shtepliuk, Guillem Domènech-Gil, Viktor Almqvist, Arja Helena Kautto, Ivar Vågsholm, Sofia Boqvist, Jens Eriksson, Donatella Puglisi

“…The model demonstrated robust predictive performance with a Kappa value of approximately 0.926, indicating near-perfect agreement between the predictions and actual classifications. …”
Get full text

Enhancing Drought Forecast Accuracy Through Informer Model Optimization by Jieru Wei, Wensheng Tang, Pakorn Ditthakit, Jiandong Shang, Hengliang Guo, Bei Zhao, Gang Wu, Yang Guo

“…Aiming at the problem of drought forecasting accuracy in a short time scale, this study proposed a drought forecasting model named VMD-JAYA-Informer based on Variational Mode Decomposition (VMD) and the JAVA optimization algorithm to improve the Informer model. This study conducted a comparative analysis of VMD-JAYA-ARIMA, VMD-JAYA-LSTM, VMD-JAYA-CNN, and VMD-JAYA-Informer drought prediction models. …”
Get full text