Predicting Alzheimer's Disease onset: A machine learning framework for early diagnosis using biomarker data by Shehu Mohammed, Neha Malhotra

“…The importance of this work is in the opportunity to shift diagnostic paradigms by employing deep learning algorithms, including CNNs, LSTM networks, and GNNs to analyze spatial, temporal, and relational patterns across multi-modal data. …”
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Faster? Softer? Or More Formal? A Study on the Methods of Enterprises’ Crisis Response on Social Media by Yongtian Yu, Weiming Ye, Kaihang Zhang

“…Algorithmic recommendation mechanisms of social media platforms, viral diffusion of user-generated content (UGC), and real-time public opinion pressures are fundamentally deconstructing the traditional corporate crisis response paradigm that used to rely on one-way statements and delayed reactions. …”
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ADPO: Adaptive DRAM Controller for Performance Optimization by Zhuorui Liu, Yan Li, Xiaoyang Zeng

“…The research methodology involves implementing a rank-level timing aware read/write turnaround arbiter and setting read/write queue thresholds and read/write turnaround settings based on observed patterns. …”
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Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…However, challenges include smaller datasets, breed variability, and limited research. Addressing these through focused research on species with less phenotypic variability (like cats) and cross-sector collaborations could advance AI in veterinary medicine. …”
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A Step-by-Step Harmonization Process for Nutritional Epidemiology Purposes: A Methodological Work of the Collaborative PROMED-COG Pooled Cohorts Study by Federica Prinelli, Silvia Conti, Claire T. McEvoy, Caterina Trevisan, Stefania Maggi, Giuseppe Sergi, Marianna Noale

“…In particular, the challenge was the harmonization procedure for dietary habits that required several steps: (i) access to documentation from the original studies, (ii) discussion with the researchers responsible for each dataset; (iii) exploration of each dataset before the final harmonization; (iv) agreement on portion size and food frequency standardization, and food classification for healthy dietary pattern computation; (v) name, definition, and categorization of the harmonized common variable and the original variables, for each study; (vi) development and application of the algorithm to obtain the harmonized variables from the original ones; and (vii) final pooled dataset preparation. …”
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Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding by Huan Liang, Xiao Liang, Man Zheng, Shoudong Wang

“…Conclusions This research elucidates the complex relationship between KLRD1 and AS, underscoring its potential as a novel biomarker for diagnosing and monitoring the disease.…”
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Review: Multiobject tracking in livestock − from farm animal management to state-of-the-art methods by M.H. Nidhi, K. Liu, K.J. Flay

“…The use-cases, datasets, and algorithms of MOT applied to livestock were thoroughly examined. …”
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The Evolution of Service Ecosystems Based on the Lotka–Volterra Model by Binbin Shi, Yu Li, Tingting Liang, Xixi Sun, Liquan Cui, Haonan Zhang, Yuyu Yin

“…At present, research on the evolution of service ecosystems largely lacks sufficient theoretical underpinning and focuses on the supply–demand relationship relationship, which reduces the credibility of research conclusions and ignores the influence of multiple factors. …”
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Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…Moreover, a comparative analysis with recent state-of-the-art algorithms highlights the competitive performance of our approaches in balancing computational efficiency and solution quality. …”
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Leveraging autoencoder models and data augmentation to uncover transcriptomic diversity of gingival keratinocytes in single cell analysis by Pradeep Kumar Yadalam, Prabhu Manickam Natarajan, Carlos M. Ardila

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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Buildings account for a substantial portion of global energy consumption, and research indicates that occupant behavior can significantly influence energy use and building performance. …”
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PREACT-digital: study protocol for a longitudinal, observational multicentre study on digital phenotypes of non-response to cognitive behavioural therapy for internalising disorder... by Christine Knaevelsrud, Sebastian Burchert, Till Langhammer, Leona Hammelrath, Annette Brose, Manuel Heinrich, Pavle Zagorscak

“…Predictive analyses focus on classification of non-response using basic algorithms (ie, logistic regression and gradient boosting) for straightforward interpretability and advanced methods (LSTM, DSEM) to capture complex temporal and hierarchical patterns. …”
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Introduction to Computational Creativity by Anna Longo, ChatGPT

“…By deconstructing the cognitive processes involved in human creativity, researchers can design algorithms that simulate these processes. …”
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Artificial Intelligence in Glioblastoma—Transforming Diagnosis and Treatment by Alen Rončević, Nenad Koruga, Anamarija Soldo Koruga, Robert Rončević

“…Limited data quality and quantity, algorithm interpretability, integration problems, and ethical considerations, remain significant challenges to clinical implementation. …”
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An integrated machine learning and fractional calculus approach to predicting diabetes risk in women by David Amilo, Khadijeh Sadri, Evren Hincal, Muhammad Farman, Kottakkaran Sooppy Nisar, Mohamed Hafez

“…We employ seven machine learning algorithms: Decision Tree, Logistic Regression, Support Vector Machine (SVM), Random Forest, Bagged Trees, Naive Bayes, and XGBoost, to identify key risk factors, with XGBoost demonstrating higher performance. …”
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Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments by Donghui Han, Tong Qin, Tianyu Yang, Hua Liao, Qiaosong Hei, Fangwen Yu, Bailu Si, Weihua Dong

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SUMOylation-related genes define prognostic subtypes in stomach adenocarcinoma: integrating single-cell analysis and machine learning analyses by Kaiping Luo, Kaiping Luo, Donghui Xing, Donghui Xing, Xiang He, Yixin Zhai, Yanan Jiang, Hongjie Zhan, Zhigang Zhao

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Analysis of the molecular nature associated with microsatellite status in colon cancer identifies clinical implications for immunotherapy by Wei Wu, Qihan Fu, Lulu Liu, Yi Zheng, Hangyu Zhang, Peng Zhao, Weijia Fang, Xuanwen Bao, Shaobing Cheng, Xiaomeng Dai, Xudong Zhu, Zhou Tong, Fanglong Liu

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Syllable-, Bigram-, and Morphology-Driven Pseudoword Generation in Greek by Kosmas Kosmidis, Vassiliki Apostolouda, Anthi Revithiadou

“…Pseudowords are essential in (psycho)linguistic research, offering a way to study language without meaning interference. …”
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High-resolution (10 m) dataset of multi-crop planting structure on the Loess Plateau during 2018–2022 by Xining Zhao, Jichao Wang, Yelu Ding, Xiaodong Gao, Changjian Li, Hongwei Huang, Xuerui Gao

“…The research methodology involved four key steps: (1) Enhancing the sample dataset using phenological indices and the Dynamic Time Warping (DTW) algorithm; (2) Identifying crop planting intensity based on phenological growth curves; (3) Developing independent random forest classifiers tailored to agricultural climate zones; and (4) Constructing an optimal feature subset for crop classification. …”
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