Leveraging a foundation model zoo for cell similarity search in oncological microscopy across devices by Gabriel Kalweit, Gabriel Kalweit, Anusha Klett, Paula Silvestrini, Paula Silvestrini, Jens Rahnfeld, Jens Rahnfeld, Mehdi Naouar, Mehdi Naouar, Yannick Vogt, Yannick Vogt, Diana Infante, Diana Infante, Rebecca Berger, Jesús Duque-Afonso, Tanja Nicole Hartmann, Marie Follo, Marie Follo, Elitsa Bodurova-Spassova, Elitsa Bodurova-Spassova, Michael Lübbert, Michael Lübbert, Roland Mertelsmann, Roland Mertelsmann, Roland Mertelsmann, Joschka Boedecker, Joschka Boedecker, Joschka Boedecker, Evelyn Ullrich, Evelyn Ullrich, Evelyn Ullrich, Maria Kalweit, Maria Kalweit

“…This especially holds true for recognizing specific cell types and states in response to treatments.ObjectiveWe aim to develop an unsupervised approach using general vision foundation models trained on diverse and extensive imaging datasets to extract rich visual features for cell-analysis across devices, including both stained and unstained live cells. …”
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Implementation of Machine Learning in Flat Die Extrusion of Polymers by Nickolas D. Polychronopoulos, Ioannis Sarris, John Vlachopoulos

“…This ML-based methodology has the potential to reduce or even eliminate the use of trial and error procedures.…”
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InGSA: integrating generalized self-attention in CNN for Alzheimer's disease classification by Faisal Binzagr, Anas W. Abulfaraj

“…The proposed InGSA is based on the InceptionV3 model which is pre-trained, and it encompasses an additional generalized self-attention (GSA) block at top of the network. …”
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An Intrusion Detection System over the IoT Data Streams Using eXplainable Artificial Intelligence (XAI) by Adel Alabbadi, Fuad Bajaber

“…DL models are needed to train enormous amounts of data and produce promising results. …”
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Dual-Mode Visual System for Brain–Computer Interfaces: Integrating SSVEP and P300 Responses by Ekgari Kasawala, Surej Mouli

“…However, conventional implementations predominantly utilise liquid crystal display (LCD)-based visual stimulation paradigms, which present limitations in practical deployment scenarios. …”
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Learning Content Model: from Concept Structuring to Adaptive Learning by J. V. Vainshtein, R. V. Esin, G. M. Tsibulsky

“…Methodological basis of research methods make up the logical-epistemological analysis and graph theory, and comparative analysis of psychological and pedagogical, scientific and methodical works, analysis of regulatory documents on research issues, professional and federal educational standards of higher education. Results. A feature of the author's approach is structuring of the subject domain in the form of a sequence of terms (training objects) of the learning content, studied in a certain order and presented in several versions of the presentation. …”
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From Narratives to Diagnosis: A Machine Learning Framework for Classifying Sleep Disorders in Aging Populations: The <i>sleepCare</i> Platform by Christos A. Frantzidis

“…First, a baseline model used a Multinomial Naïve Bayes classifier with n-gram features from a Bag-of-Words representation. Next, a Support Vector Machine (SVM) was trained on GloVe-based word embeddings to capture semantic context. …”
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Development and validation of a machine learning model for predicting pulmonary metastasis in hepatocellular carcinoma patients by Gangfeng Zhu, Qiang Yi, Rui Xu, Yi Xie, Siying Chen, Yipeng Song, Yi Xiang, Xiangcai Wang, Li Huang

“…Based on the RF algorithm, we developed a user-friendly, web-based tool to estimate the risk of pulmonary metastasis in patients with HCC. …”
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ARC-LIGHT: Algorithm for Robust Characterization of Lunar Surface Imaging for Ground Hazards and Trajectory by Alexander Cushen, Ariana Bueno, Samuel Carrico, Corrydon Wettstein, Jaykumar Ishvarbhai Adalja, Mengxiang Shi, Naila Garcia, Yuliana Garcia, Mirko Gamba, Christopher Ruf

“…Based on these findings, a development timeline, risk analysis, and budget for ARC-LIGHT to be deployed on a lunar landing was created.…”
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AI-Powered Structural Health Monitoring: Predicting Fatigue Damage in Aircraft Composites with Ultrasonic Guided Wave Inspections by Panagiotis Kolozis, Dimitrios Karasavvas, José Manuel Royo, Javier Hernandez-Olivan, Vanessa Thalassinou-Lislevand, Andrea Calvo-Echenique, Elias Koumoulos

“…The signals captured by the piezoelectric sensors are utilized to engineer key features sensitive to composite structural damage, which are then used to train a deep neural network (DNN) for accurate structural damage prediction. …”
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Deep Learning Models and Fusion Classification Technique for Accurate Diagnosis of Retinopathy of Prematurity in Preterm Newborn by Nazar Salih, Mohamed Ksantini, Nebras Hussein, Donia Ben Halima, ali Abdul Razzaq, Sohaib Ahmed

“…   Retinopathy of prematurity (ROP) is the most common cause of irreversible childhood blindness, and its diagnosis and treatment rely on subjective grading based on retinal vascular features. However, this method is laborious and error-prone, so automated approaches are desirable for greater precision and productivity. …”
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Feasibility of snapshot testing using wearable sensors to detect cardiorespiratory illness (COVID infection in India) by Olivia K. Botonis, Jonathan Mendley, Shreya Aalla, Nicole C. Veit, Michael Fanton, JongYoon Lee, Vikrant Tripathi, Venkatesh Pandi, Akash Khobragade, Sunil Chaudhary, Amitav Chaudhuri, Vaidyanathan Narayanan, Shuai Xu, Hyoyoung Jeong, John A. Rogers, Arun Jayaraman

“…Abstract The COVID-19 pandemic has challenged the current paradigm of clinical and community-based disease detection. We present a multimodal wearable sensor system paired with a two-minute, movement-based activity sequence that successfully captures a snapshot of physiological data (including cardiac, respiratory, temperature, and percent oxygen saturation). …”
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Accurate deep-learning model to differentiate dementia severity and diagnosis using a portable electroencephalography device by Masahiro Hata, Takufumi Yanagisawa, Yuki Miyazaki, Hisaki Omori, Atsuya Hirashima, Yuta Nakagawa, Mitsuhiro Eto, Kenji Yoshiyama, Hideki Kanemoto, Byambadorj Nyamradnaa, Shusuke Yoshimoto, Kotaro Ezure, Shun Takahashi, Manabu Ikeda

“…We analyzed EEG data from 233 participants, including 119 HVs and 114 patients, and transformed the signals into frequency-domain features using a short-time Fourier transform. A customized transformer-based model was trained and evaluated using 10-fold cross-validation and a holdout dataset. …”
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Making a Real-Time IoT Network Intrusion-Detection System (INIDS) Using a Realistic BoT–IoT Dataset with Multiple Machine-Learning Classifiers by Jawad Ashraf, Ghulam Musa Raza, Byung-Seo Kim, Abdul Wahid, Hye-Young Kim

“…Most existing machine-learning-based intrusion-detection systems for IoT have been trained using outdated datasets that do not accurately reflect IoT scenarios. …”
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From laboratory to field: cross-domain few-shot learning for crop disease identification in the field by Sen Yang, Quan Feng, Jianhua Zhang, Wanxia Yang, Wenwei Zhou, Wenbo Yan

“…Within this framework, three representative CD-FSL models were developed by integrating the Brownian distance covariance (BCD) module and improving the general feature extractor, namely metric-based CD-FSL(CDFSL-BDC), optimization-based CD-FSL(CDFSL-MAML), and non-meta-learning-based CD-FSL (CDFSL-NML). …”
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AxonFinder: Automated segmentation of tumor innervating neuronal fibers by Kaoutar Ait-Ahmad, Cigdem Ak, Guillaume Thibault, Young Hwan Chang, Sebnem Ece Eksi

“…We present a novel deep learning-based approach for the automated segmentation of axons, AxonFinder, leveraging a U-Net model with a ResNet-101 encoder, based on a multiplexed imaging approach. …”
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Infrared image monitoring algorithm for converter valve equipment by Jiashui Dai, Fali Tan, Yi Jiang, Yunlong Liang, Kangquan Lin, Kai Tong

“…The normalized data are combined with the time and temperature data and input into the BiLSTM model for training. According to the high requirements for the target detection algorithm in the converter valve scenario, lightweight PConv convolution is introduced to improve the C2f module of YOLOv8n, and Slim-neck improvement of the feature fusion layer is made. …”
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EDITORIAL by Ivan Čuk

“…Our journal has been recently entered into the ErihPlus data base for humanities and social sciences. The process of evaluation took more than half a year but was successfully completed. …”
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Development and validation of a nomogram for predicting diabetic foot ulcer risk in patients with type 2 diabetes mellitus by Xiuli Feng, Renhao Zhao, Teng Yang, Na Wang, Guofeng Wang

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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

“…Principal component analysis is also utilized (PCA) to extract features, hence expediting the entire process by reducing dimensionality. …”
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