Multimodal diagnostic tools and advanced data models for detection of prodromal Parkinson’s disease: a scoping review by Ibrahim Serag, Ahmed Y. Azzam, Amr K. Hassan, Rehab Adel Diab, Mohamed Diab, Mahmoud Tarek Hefnawy, Mohamed Ahmed Ali, Ahmed Negida

“…The diagnosis of prodromal PD remains challenging despite many available diagnostic modalities. Aim This scoping review aims to investigate and explore the current diagnostic modalities used to detect prodromal PD, focusing particularly on multimodal imaging analysis and AI-based approaches. …”
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Impact of a health campaign on Chinese public awareness of stroke: evidence from internet search data by Yuanli Liu, Xueyan Han, Man Cao, Tianjia Guan, Bingjie Shen, Baohua Chao

“…This study aimed to measure the impact of World Stroke Day (WSD) in China using Baidu search data.Methods Daily search index values (SIV) for the term ‘stroke’ were collected from January 2011 to December 2019 using the Baidu Index platform. …”
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Sentiment Analysis of Pro-Israel Product Boycott Action Using IndoBERT Method on Unbalanced Data by Auliana Rizky Puspita Dewi, Slamet Riyadi, Cahya Darmajati, Nor Ashidi Mat Isa, Annisa Divayu Andriyani

“…Therefore, this study aimed to develop a sentiment analysis model using the IndoBERT method with more data to examine sentiments related to the boycott of Pro-Israel products on Twitter using imbalanced data, as well as to evaluate the effect of balancing methods using under sampling and oversampling on the model’s accuracy and performance. …”
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A data driven approach for soft tissue biomarker identification linked to Chiari-like malformation and syringomyelia by Jake Cumber, Jake Cumber, Emma Scales-Theobald, Emma Scales-Theobald, Clare Rusbridge, Clare Rusbridge, Clare Rusbridge, Kevin Wells, Kevin Wells

“…These results contribute to the further understanding of the complex pathologies associated with CM and SM in brachycephalic toy pure and mixed breed dogs and support the potential utility of data-driven techniques for advancing our knowledge of these debilitating conditions.…”
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DeepExtremeCubes: Earth system spatio-temporal data for assessing compound heatwave and drought impacts by Chaonan Ji, Tonio Fincke, Vitus Benson, Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Fabian Gans, Guido Kraemer, Francesco Martinuzzi, David Montero, Karin Mora, Oscar J. Pellicer-Valero, Claire Robin, Maximilian Söchting, Mélanie Weynants, Miguel D. Mahecha

“…Each minicube includes (i) Sentinel-2 L2A images, (ii) ERA5-Land variables and generated extreme event cube covering 2016 to 2022, and (iii) ancillary land cover and topography maps. The paper aims to (1) streamline data accessibility, structuring, pre-processing, and enhance scientific reproducibility, and (2) facilitate biosphere dynamics forecasting in response to compound extremes.…”
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A natural language processing approach to support biomedical data harmonization: Leveraging large language models. by Zexu Li, Suraj P Prabhu, Zachary T Popp, Shubhi S Jain, Vijetha Balakundi, Ting Fang Alvin Ang, Rhoda Au, Jinying Chen

“…<h4>Conclusion</h4>NLP techniques (especially LLMs), combined with ensemble learning, hold great potential in automating variable matching and accelerating biomedical data harmonization.…”
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Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size. by Valter Cesar de Souza, Sergio Augusto Rodrigues, Luís Roberto Almeida Gabriel Filho

“…Future research should explore the effectiveness of various imputation methods in diverse climatic and geographical contexts, as well as develop new techniques considering the temporal and spatial structure of meteorological data, to advance understanding and climate prediction.…”
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Predicting determinants of unimproved water supply in Ethiopia using machine learning analysis of EDHS-2019 data by Jember Azanaw, Mihret Melese, Eshetu Abera Worede

“…This study aimed to provide more accurate predictions and data-driven insights that can inform policy-making, resource allocation, and interventions to address Ethiopia’s water crisis. …”
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Identifying High-Risk Intersections for Walking and Bicycling Using Multiple Data Sources in the City of San Diego by Mahdie Hasani, Arash Jahangiri, Ipek Nese Sener, Sirajum Munira, Justin M. Owens, Bruce Appleyard, Sherry Ryan, Shawn M. Turner, Sahar Ghanipoor Machiani

“…Data mining techniques, a new sampling strategy, and automated video processing methods were adopted to demonstrate a holistic approach that can be applied to identify facilities with highest need of improvement. …”
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Examining the Impact of Content Features on Customer Engagement in Social Media: A Data Mining Approach on Instagram by Azade Shekari, Mohammad Mehdi Poursaeed, Saeed Dehyadegari

“…Methodology Considering the huge amount of content produced on social networks, one of the best methods to analyze and identify patterns in these networks is data mining techniques. To achieve this goal, visual and textual features of 490 content pieces published on the commercial pages of cosmetics products from the Cinere, Lisel, Schon, and Bioderma brands were collected. …”
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Precision diagnosis of tomato diseases for sustainable agriculture through deep learning approach with hybrid data augmentation by Kamaldeep Joshi, Sahil Hooda, Archana Sharma, Humira Sonah, Rupesh Deshmukh, Narendra Tuteja, Sarvajeet Singh Gill, Ritu Gill

“…However, the scarcity of real-world data hampers effectiveness. To address this issue, data augmentation techniques simulate variations in farm images, enriching datasets for improved detection of diseases. …”
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Assessing national exposure to and impact of glacial lake outburst floods considering uncertainty under data sparsity by H. Chen, Q. Liang, J. Zhao, S. B. Maharjan

“…This study aims to exploit remote sensing techniques, well-established Bayesian regression models for estimating glacial lake conditions, cutting-edge flood modelling technology, and open data from various sources to innovate a framework for assessing the national exposure and impact of GLOFs. …”
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Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis by Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani, Adetokunbo Arogbonlo, Siamak Pedrammehr, Adnan Anwar, Hailing Zhou, Lei Wei, Asim Bhatti, Sam Oladazimi, Burhan Khan, Saeid Nahavandi

“…Various machine learning classification techniques have been utilized to distinguish cognitive states. …”
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Microvascular Metrics on Diabetic Retinopathy Severity: Analysis of Diabetic Eye Images from Real-World Data by Cristina Cuscó, Pau Esteve-Bricullé, Ana Almazán-Moga, Jimena Fernández-Carneado, Berta Ponsati

“…<b>Objective:</b> To quantify microvascular lesions in a large real-world data (RWD) set, based on single central retinal fundus images of diabetic eyes from different origins, with the aim of validating its use as a precision tool for classifying diabetic retinopathy (DR) severity. …”
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Harnessing Digital Technologies for Rural Industrial Integration: A Pathway to Sustainable Growth by Jingkun Zhang, Wang Zhang

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Development of Digital NDT Methodology: Data Augmentation for Automated Fluorescent Penetrant Inspection of Aircraft Engine Blades by Milan T. Bril, Daniel Friesen, Konstantinos Stamoulis

“…In this paper, we propose a data augmentation technique named Mosaic to artificially create more training data. …”
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Efficiency of night shifts in Primary Healthcare Centers, Aseer Region, Saudi Arabia: Data envelopment analysis by Abdullah A. Saeed, Yahia M. Al Khaldi, Tariq A.I. Falqi, Mohammed A. Qarnan, Zaid S. Alharthi, Abdullah A. Alshafea

“…Study employed a quantitative approach and the data envelopment analysis technique to assess the efficiency of PHCCs, specifically focusing on night shift performance. …”
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Data mining of Students Withdrawal at University of Tehran, Focusing on Fee Paid Students (to prevent customer churn) by Saied Ali Akbar Ahmadi, Davood Karimzadgan, Toraj Khairati Kazerooni

“…This study is a descriptive an applicable technique that uses quantitative and qualitative data. …”
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Analysis of meteorological effects of cosmic ray neutron component based on data from mid-latitude stations by Kobelev P. G., Hamraev Y. B., Yanke V. G.

“…The technique developed on the basis of multifactor correlation analysis is applicable to processing data from any detectors of the worldwide network of neutron monitors. …”
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An exploratory analysis of longitudinal artificial intelligence for cognitive fatigue detection using neurophysiological based biosignal data by Sameer Nooh, Mahmoud Ragab, Rania Aboalela, Abdullah AL-Malaise AL-Ghamdi, Omar A. Abdulkader, Ghadah Alghamdi

“…Therefore, the study presents an Exploratory Analysis of Longitudinal Artificial Intelligence for Cognitive Fatigue Detection Using Neurophysiological Based Biosignal Data (EALAI-CFDNBD) approach. The main aim of the EALAI-CFDNBD model is to detect cognitive fatigue using neurophysiological-based biosignal data. …”
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