Multimodal AI in Biomedicine: Pioneering the Future of Biomaterials, Diagnostics, and Personalized Healthcare by Nargish Parvin, Sang Woo Joo, Jae Hak Jung, Tapas K. Mandal

“…Advanced tools like AlphaFold have significantly improved protein structure prediction, enabling the creation of biomaterials with enhanced biological compatibility. …”
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Enhancing Hazard Detection and Risk Severity Assessment in Construction through Multinomial Naive Bayes and Regression by Akaninyene Michael Akwaisua, Anietie Ekong, Godwin Ansa

“…Using the Linear Regression algorithm, the model predicts the severity of risks based on textual descriptions of a hazard.  …”
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Machine learning-based analysis on pharmaceutical compounds interaction with polymer to estimate drug solubility in formulations by Ahmad J. Obaidullah, Wael A. Mahdi

“…Hyperparameter tuning is rigorously conducted utilizing the Harmony Search (HS) algorithm. For drug solubility prediction, the ADA-DT model demonstrates superior performance, achieving an R² score of 0.9738 on the test set, with a Mean Squared Error (MSE) of 5.4270E-04 and a Mean Absolute Error (MAE) of 2.10921E-02. …”
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Graph neural network-based water contamination detection from community housing information by Raphael Anaadumba, Yigit Bozkurt, Connor Sullivan, Madhavi Pagare, Pradeep Kurup, Benyuan Liu, Mohammad Arif Ul Alam

“…Specifically, the GAT achieved an accuracy of 0.80, precision of 0.71, and recall of 0.93, outperforming XGBoost, a classical machine learning algorithm, which had an accuracy of 0.70, precision of 0.66, and recall of 0.67.Discussion: In addition to its predictive capabilities, the GAT model identifies key factors contributing to lead contamination, enabling more precise targeting of at-risk areas. …”
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Face Identification Based on K-Nearest Neighbor by Ni Kadek Ayu Wirdiani, Praba Hridayami, Ni Putu Ayu Widiari, Komang Diva Rismawan, Putu Bagus Candradinata, I Putu Deva Jayantha

“…The K-Nearest Neighbor algorithm uses neighborhood classification as the predictive value of a good instance value. …”
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Machine learning analysis of rivaroxaban solubility in mixed solvents for application in pharmaceutical crystallization by Mohammed Alqarni, Ali Alqarni

“…Abstract This study investigates the use of machine learning models to predict solubility of rivaroxaban in binary solvents based on temperature (T), mass fraction (w), and solvent type. …”
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Credit Rating Model Based on Improved TabNet by Shijie Wang, Xueyong Zhang

“…Under the rapid evolution of financial technology, traditional credit risk management paradigms relying on expert experience and singular algorithmic architectures have proven inadequate in addressing complex decision-making demands arising from dynamically correlated multidimensional risk factors and heterogeneous data fusion. …”
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Control system design for azimuth position of earth station antennas by Auday Al-Mayyahi, Ammar Aldair, Zainab A. Khalaf, William Wang

“…The camel optimization algorithm (COA) was used to obtain the optimal design parameters of each controller in the considered scenarios.…”
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Artificial Intelligence for Financial Accountability and Governance in the Public Sector: Strategic Opportunities and Challenges by Ceray Aldemir, Tuğba Uçma Uysal

“…However, challenges such as algorithmic bias, data privacy issues, and the need for strong ethical guidelines still exist, and these could hinder the equitable use of AI. …”
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Machine learning approach for studying the neural underpinnings of dyslexia on a phonological awareness task by Christoforos Christoforou, Timothy C. Papadopoulos, Maria Theodorou

“…Results showed that the proposed phoneme-related neural-congruency components are predictive about the underlying neuronal differences amongst groups. …”
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Dense Crowd Dynamics and Pedestrian Trajectories: A Multiscale Field Dataset from the Festival of Lights in Lyon by Oscar Dufour, Huu-Tu Dang, Jakob Cordes, Raphael Korbmacher, Mohcine Chraibi, Benoit Gaudou, Alexandre Nicolas, Antoine Tordeux

“…Abstract The dynamics of dense crowds have received considerable attention from researchers seeking fundamental understanding or aiming to develop data-driven algorithms to predict pedestrian trajectories. However, current research mainly relies on data collected in controlled settings. …”
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Impact Analysis of BIM on Power Substation Project Costs: Techno-Economic Data Evidence from China by Ding Liu, Lizhong Qi, Yi Sun, Jingguo Rong, Su Zhang, Guangze Yu

“…To this end, this study collected total project cost data from 164 power substation projects and techno-economic statements from 34 power substation projects from SGCC to capture data evidence of the impact of BIM on project costs and explore its patterns. Algorithms such as hierarchical clustering based on improved DTW and feature selection based on QDA were designed for data mining. …”
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Impact of Airborne Radio Occultation Observations on Short Term Precipitation Forecasts of an Atmospheric River by Phuong‐Nghi Do, Jennifer S. Haase, Ivette Hernández Baños, Pawel Hordyniec, Bing Cao

“…This study evaluates the impact of assimilating ARO bending angle observations using the Model for Prediction Across Scales—Atmosphere—Joint Effort for Data assimilation Integration (MPAS‐JEDI). …”
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AI-Driven Future Farming: Achieving Climate-Smart and Sustainable Agriculture by Karishma Kumari, Ali Mirzakhani Nafchi, Salman Mirzaee, Ahmed Abdalla

“…Using sophisticated algorithms to predict soil conditions, improving agricultural yield projections, diagnosing water stress from sensor data, and identifying plant diseases and weeds through image recognition, crop mapping, and AI-guided crop selection are some of the main applications investigated. …”
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Testing the Perturbation Sensitivity of Abortion-Crime Regressions by Michał Brzeziński, Maria Halber

“…The hypothesis that the legalisation of abortion contributed significantly to the reduction of crime in the United States in 1990s is one of the most prominent ideas from the recent “economics-made-fun” movement sparked by the book Freakonomics. …”
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Ensemble stacking: a powerful tool for landslide susceptibility assessment – a case study in Anhua County, Hunan Province, China by Lei-Lei Liu, Aasim Danish, Xiao-Mi Wang, Wen-Qing Zhu

“…In this study, we evaluate and compare the effectiveness of six machine learning algorithms for predicting landslide susceptibility in Anhua County, Hunan Province, China. …”
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Balanced operation strategies of district heating systems based on dynamic hydraulic-thermal modeling by Xiaojie Lin, Ning Zhang, Zheng Luo, Encheng Feng, Wei Zhong

“…The heating supply imbalance of the primary side return temperatures among different heating substations is defined and optimized based on the dynamic hydraulic-thermal model and the particle swarm optimization algorithm. In the case analysis, the results of heating supply imbalance before and after optimization are 0.81 K and 0.47 K, respectively, with a 42.0 % reduction in heating imbalances after optimization. …”
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Multistage power generation planning approach for new power systems with high renewable energy integration considering flexibility constraints by Danyang Li, Hongpeng Liu, Jingwei Zhang, Xu Han, Shuxin Zhang

“…A flexibility-constrained multi-stage generation planning model is formulated, which resolves nonlinearity through auxiliary variable linearization and Benders decomposition algorithm. Case studies demonstrate that the proposed model achieves a 47.3% reduction in total 10-year planning costs for a typical regional system, comprising 39.5% operational cost savings and 46.3% carbon emission cost reduction, while elevating renewable energy accommodation rate to 80%. …”
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A novel transformer-based approach for cardiovascular disease detection by Nimra Noor, Muhammad Bilal, Saadullah Farooq Abbasi, Omid Pournik, Theodoros N. Arvanitis

“…The proposed study achieved a maximum accuracy, precision, recall, and F1 score of 0.9979, 0.9959, 0.9958, and 0.9959, respectively. The proposed algorithm outperformed all the existing state-of-the-art algorithms for CVD classification.…”
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Deep‐NCA: A deep learning methodology for performing noncompartmental analysis of pharmacokinetic data by Gengbo Liu, Logan Brooks, John Canty, Dan Lu, Jin Y. Jin, James Lu

“…Although the existing NCA algorithms are very well‐established and widely utilized, they suffer from low accuracies in the setting of sparse PK samples. …”
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