Neuroimaging informatics framework for analyzing rare brain metastasis patterns in pleural mesothelioma using hybrid PET CT by Sumit Kumar Agrawal, Indra Prakash Dubey, Anoop Kumar Nair, Anurag Jain, Abhishek Mahato, Rajeev Kumar

“…While a radiomics pipeline drives out quantitative characteristics like texture, intensity, and shape descriptors, a deep learning (DL)-based segmentation algorithm finds abnormal metabolic activity suggestive of metastatic lesions. …”
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Development of prediction models for screening depression and anxiety using smartphone and wearable-based digital phenotyping: protocol for the Smartphone and Wearable Assessment f... by Sujin Kim, Ah Young Kim, Yu-Bin Shin, Seonmin Kim, Min-Sup Shin, Jinhwa Choi, Kyung Lyun Lee, Jisu Lee, Sangwon Byun, Heon-Jeong Lee, Chul-Hyun Cho

“…The primary outcome will be the development of machine-learning algorithms to predict depression and anxiety based on these digital biomarkers. …”
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Advanced imaging techniques and artificial intelligence in pleural diseases: a narrative review by Guido Marchi, Mattia Mercier, Jacopo Cefalo, Carmine Salerni, Martina Ferioli, Piero Candoli, Leonardo Gori, Federico Cucchiara, Giovanni Cenerini, Giacomo Guglielmi, Michele Mondoni

“…The integration of AI-driven imaging analysis with molecular and genomic data offers potential for personalised therapeutic strategies, although challenges in data privacy, algorithm transparency and clinical validation persist. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…Advances in AI, mainly in machine learning and deep learning, have significantly influenced medical research and clinical practice over the past decades by offering precisions in data understanding and treatment approaches. …”
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Hybrid neural network method for damage localization in structural health monitoring by Fatahlla Moreh, Yusuf Hasan, Zarghaam Haider Rizvi, Sven Tomforde, Frank Wuttke

“…Many existing methods for crack detection rely on deep learning algorithms or traditional approaches that typically use image data. …”
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A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy by Barbora Salovska, Wenxue Li, Oliver M. Bernhardt, Pierre-Luc Germain, Qinyue Wang, Tejas Gandhi, Lukas Reiter, Yansheng Liu

“…Previous multiplex-DIA-MS workflows have employed various strategies including leveraging the highest isotopic labeling channels to enhance the detection of isotopic signal pairs. Here we present a robust workflow that integrates a machine learning algorithm and channel-specific statistical filtering, enabling dynamic adaptation to channel ratio changes across multiplexed experiments and enhancing both coverage and accuracy of protein turnover profiling. …”
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Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition by Libang Chen, Jinyan Lin, Qihang Bian, Yikun Liu, Jianying Zhou

“…Maximum Histogram Equalization (MHE) is used to achieve high contrast while maintaining fidelity to the original content. We evaluated our algorithm using data collected from both a fog chamber and outdoor environments and performed comparative analyses with existing methods. …”
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Method of troubleshooting in the neural network environment of intellectual decision supporting systems by О.І. Тимочко, С.В. Осієвський, О.О. Тімочко, П.В. Бєляєв

“…It is shown that to detect these types of errors it is advisable to use a modified GLARE algorithm with the adaptation procedure. …”
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Deep Point Cloud Facet Segmentation and Applications in Downsampling and Crop Organ Extraction by Yixuan Wang, Chuang Huang, Dawei Li

“…By using a learned facet classifier to filter out and discard empty facets, retaining only non-empty surface facets, and fusing point coordinates and local features within each facet, the method achieves significant compression of point cloud data while preserving essential geometric information. …”
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Research on the Optimization of the Electrode Structure and Signal Processing Method of the Field Mill Type Electric Field Sensor by Wei Zhao, Zhizhong Li, Haitao Zhang

“…An improved harmonic detection method combining fast Fourier transform and back propagation neural network (FFT-BP) was proposed, the learning rate, momentum factor, and excitation function jointly participated in the adjustment of the network, and the iterative search range of the algorithm was limited by the threshold interval, further improving the accuracy and rapidity of the sensor measurement. …”
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Nuevos modelos para la Caracterización, Detección y Diagnóstico de Fallas en Máquinas Eléctricas Rotativas by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…The main objective is to explore and propose new methodologies for characterizing faults in electric motors through the use of data analysis and machine learning techniques, reviewing traditional and current methods for fault diagnosis, including vibration analysis techniques and supervised and unsupervised learning algorithms. …”
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Study on the mechanisms associating community outdoor public spaces with elderly behavior by Lei Wang, Wenqi He, Shan Wu, Bo Zhang, Xiaorui Zhang, Hu Yin

“…A computer vision-based behavior detection algorithm is then constructed to effectively identify six typical activities of the elderly: exercising, jogging, sitting, standing, walking, and playing chess or cards. …”
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Efficient diagnosis of diabetes mellitus using an improved ensemble method by Blessing Oluwatobi Olorunfemi, Adewale Opeoluwa Ogunde, Ahmad Almogren, Abidemi Emmanuel Adeniyi, Sunday Adeola Ajagbe, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Asif Mehmood, Habib Hamam

“…Abstract Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. …”
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Concordance and test-retest consistency of sleep biomarker-based neurodegenerative disorder profiling by Daniel J. Levendowski, Debby Tsuang, Lana M. Chahine, Christine M. Walsh, Chris Berka, Joyce K. Lee-Iannotti, David Salat, Corrine Fischer, Gandis Mazeika, Bradley F. Boeve, Luigi Ferini Strambi, Simon J. G. Lewis, Thomas C. Neylan, Erik K. St. Louis

“…The algorithm was validated in a total of 381 recordings, which included the training data set plus an additional AD = 10, iRBD = 18, Parkinson disease without dementia (PD = 29), mild cognitive impairment (MCI = 78) and CG = 128. …”
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Artificial intelligence based surgical support for experimental laparoscopic Nissen fundoplication by Holger Till, Ciro Esposito, Chung Kwong Yeung, Dariusz Patkowski, Sameh Shehata, Steve Rothenberg, Georg Singer, Tristan Till

“…BackgroundComputer vision (CV), a subset of artificial intelligence (AI), enables deep learning models to detect specific events within digital images or videos. …”
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Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells. by Owen M O'Connor, Mary J Dunlop

“…Deep learning-based methods for identifying and tracking cells within microscopy images have revolutionized the speed and throughput of data analysis. …”
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OCTNet: A Modified Multi-Scale Attention Feature Fusion Network with InceptionV3 for Retinal OCT Image Classification by Irshad Khalil, Asif Mehmood, Hyunchul Kim, Jungsuk Kim

“…Traditional approaches rely on machine learning for feature extraction, while deep learning methods utilize data-driven classification model training. …”
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A novel ensemble of hybrid starling murmuration optimized stacked gated Ghostnets for robust classification of DDoS attacks by P. Mamatha, S. Balaji, S. Sai Anuraghav

“…The proposed ensemble learning approaches with the SMO tuned hyper-parameters yield superior detection performance. …”
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Digital Image Copyright Protection and Management Approach—Based on Artificial Intelligence and Blockchain Technology by Jikuan Xu, Jiamin Zhang, Junhan Wang

“…It introduces an originality detection model based on deep learning technology after conducting both off-chain and on-chain detection of unidentified images, providing triple protection for digital image copyright infringement detection and enabling efficient active defense and passive evidence storage. …”
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COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

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