A deep multiple instance learning framework improves microsatellite instability detection from tumor next generation sequencing by John Ziegler, Jaclyn F. Hechtman, Satshil Rana, Ryan N. Ptashkin, Gowtham Jayakumaran, Sumit Middha, Shweta S. Chavan, Chad Vanderbilt, Deborah DeLair, Jacklyn Casanova, Jinru Shia, Nicole DeGroat, Ryma Benayed, Marc Ladanyi, Michael F. Berger, Thomas J. Fuchs, A. Rose Brannon, Ahmet Zehir

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Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015–2018 by Danhui Mao, Junfang Mu, Yajing Li, Lu He, Qianhui Chai, Xin Zhao, Xiaojun Ren, Hui Cheng

“…This study used Louvain and machine learning algorithm for CMM pattern detection. The features playing key roles in CMM pattern recognition included choline, iron, niacin, cholesterol, Vitamin B2 and potassium intake, which can serve as references for CMM health management.…”
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Drone-assisted adaptive object detection and privacy-preserving surveillance in smart cities using whale-optimized deep reinforcement learning techniques by Ahmed Abu-Khadrah, Ahmad Al-Qerem, Mohammad R. Hassan, Ali Mohd Ali, Muath Jarrah

“…The optimization algorithm detects spreading image features from the origin to the end of x×y pixels. …”
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Lightweight and rapid adaptive super-resolution interpolation reconstruction algorithm for super-pixel segmentation of super-wide field-of-view long-wave infrared images by Dongdong Shi, Xia Cai, Limin Liu, Fuyu Huang, Kangli Xu, Yuanbo Wang, Yudan Chen

“…In addition, the Vollath parameter, Roberts parameter, and Laplace parameter increase by 7.16%, 14.84%, and 15.62%, respectively. Furthermore, our algorithm in this paper has certain advantages, such as low-intensity noise and a calculation time of around 0.5 s, making it have certain application value for the SWFOV LWIR imaging system that requires real-time high-definition imaging.…”
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Point-Of-Care low-field MRI in acute Stroke (POCS): protocol for a multicentric prospective open-label study evaluating diagnostic accuracy by Mauro Silvestrini, Simona Sacco, Massimo Caulo, Simona Marcheselli, Carmine Marini, Sergio Lucio Vinci, Angelo Galante, Marco Colasurdo, Raffaele Ornello, Matteo Foschi, Stefano Necozione, Mario Muselli, Paola Olimpia Achard, Luciano Fratocchi, Marco Cavallaro, Gabriele Polonara, Laura Straffi, Luca Sorrentino, Enrico Franconi, Marcello Alecci

“…Rapid access to HF-MRI is often limited by contraindications or unavailability. Low-field (LF) MRI (<0.5T) can detect several types of brain injury, including ischaemic and haemorrhagic stroke. …”
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Development of a Drone-Based Phenotyping System for European Pear Rust (<i>Gymnosporangium sabinae</i>) in Orchards by Virginia Maß, Johannes Seidl-Schulz, Matthias Leipnitz, Eric Fritzsche, Martin Geyer, Michael Pflanz, Stefanie Reim

“…A total of 16,251 annotations of leaves with pear rust symptoms were created on 584 images using the Computer Vision Annotation Tool (CVAT). The YOLO algorithm was used for the automatic detection of symptoms. …”
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Characterization of Historical Aerosol Optical Depth Dynamics Using LSTM and Peak Enhancement Techniques by Horia-Alexandru Cămărășan, Alexandru Mereuță, Lucia-Timea Deaconu, Horațiu-Ioan Ștefănie, Andrei-Titus Radovici, Camelia Botezan, Zoltán Török, Nicolae Ajtai

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A hybrid optimization-enhanced 1D-ResCNN framework for epileptic spike detection in scalp EEG signals by Priyaranjan Kumar, Prabhat Kumar Upadhyay

“…The false positive rate (FPR) remained low at 0.0011, and the model obtained an average F1-score of 99.74%. …”
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DBSANet: A Dual-Branch Semantic Aggregation Network Integrating CNNs and Transformers for Landslide Detection in Remote Sensing Images by Yankui Li, Wu Zhu, Jing Wu, Ruixuan Zhang, Xueyong Xu, Ye Zhou

“…Deep learning-based semantic segmentation algorithms have proven effective in landslide detection. …”
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Comparative analysis of hybrid-SNP microarray and nanopore sequencing for detection of large-sized copy number variants in the human genome by Catarina Silva, José Ferrão, Bárbara Marques, Sónia Pedro, Hildeberto Correia, Ana Valente, António Sebastião Rodrigues, Luís Vieira

“…In the 10 CNV not called in nanopore sequencing, 8 showed coverage evidence of genomic loss or gain, highlighting the need to improve SV calling algorithms performance. Conclusions Nanopore sequencing offers advantages over CMA for structural variant detection, including the identification of multiple variant types and their breakpoints with increased precision. …”
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Detection of IgM, IgG and IgA against pertussis in pregnant women in I - II - III trimesters by T. A. Skirda, O. Yu. Borisova, N. T. Gadua, A. S. Pimenova, I. I. Mekhant'ev, Yu. I. Stepkin, I. M. Degtyareva, S. V. Bredihin, M. S. Petrova, A. B. Borisova, A. V. Safronova, S. Yu. Kombarova

“…Anti-pertussis IgG concentration below the low limit of detection occurred in 75,7% of pregnant women. …”
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Computer vision applications for the detection or analysis of tuberculosis using digitised human lung tissue images - a systematic review by Kapongo D. Lumamba, Gordon Wells, Delon Naicker, Threnesan Naidoo, Adrie J. C. Steyn, Mandlenkosi Gwetu

“…The ultimate goal is to promote the development of more efficient and accurate algorithms for the detection or analysis of TB, and raise awareness about the importance of early detection. …”
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Impact of cardiopulmonary resuscitation on a cannot intubate, cannot oxygenate condition: a randomised crossover simulation research study of the interaction between two algorithms by Thomas Ott, Jascha Stracke, Susanna Sellin, Marc Kriege, Gerrit Toenges, Carsten Lott, Sebastian Kuhn, Kristin Engelhard

“…In this stressful situation, two complex algorithms facilitate decision-making to save a patient’s life: difficult airway management and cardiopulmonary resuscitation. …”
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Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

“…To address these challenges, we developed Tiny Machine Learning (TinyML) models for the real-time detection of respiratory conditions by using lung sound recordings, deployable on low-power, cost-effective devices like digital stethoscopes. …”
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Human multiethnic radiogenomics reveals low-abundancy microRNA signature in plasma-derived extracellular vesicles for early diagnosis and molecular subtyping of pancreatic cancer by Jianying Xu, Wenjie Shi, Yi Zhu, Chao Zhang, Julia Nagelschmitz, Maximilian Doelling, Sara Al-Madhi, Ujjwal Mukund Mahajan, Maciej Pech, Georg Rose, Roland Siegfried Croner, Guoliang Zheng, Christoph Kahlert, Ulf Dietrich Kahlert

“…Radiomics-related low-abundance EV miRNAs were identified via weighted gene co-expression network analysis and validated for diagnostic accuracy using 10 machine-learning algorithms. …”
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MF-ShipNet: a multi-feature weighted fusion and PCA-SVM model for ship detection in remote sensing images by Jianfeng Li, Yibing Yang, Liutong Yang, Yang Zhao, Qinghua Luo, Chenxu Wang

“…Due to the complex sea background and the different sizes and shapes of ships, the detection of ship targets has the problems of low detection rate, high false detection rate and high missed detection rate. …”
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Binocular Video-Based Automatic Pixel-Level Crack Detection and Quantification Using Deep Convolutional Neural Networks for Concrete Structures by Liqu Liu, Bo Shen, Shuchen Huang, Runlin Liu, Weizhang Liao, Bin Wang, Shuo Diao

“…Crack detection and quantification play crucial roles in assessing the condition of concrete structures. …”
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Efficient Switched-Beam Detection for Dynamic Spectrum Sharing in 6G Wireless Networks With Full Duplex Technology at the THz Band by Andrea Tani, Dania Marabissi

“…Compared to the recursive least squares (RLS) adaptive filtering benchmark, it offers a more robust false alarm probability, particularly in the low-AWGN regime, with detection performance similar to or slightly lower than the RLS detector, but with significantly lower computational complexity.…”
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Unique temperature change patterns in calves eyes and muzzles: a non-invasive approach using infrared thermography and object detection by Sueun Kim, Norio Yamagishi, Shingo Ishikawa, Shinobu Tsuchiaka

“…A mobile thermal imaging camera was paired with the Mask R-CNN algorithm (object detection) trained on annotated datasets to detect eye and muzzle regions accurately. …”
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Detecting severe coronary artery stenosis in T2DM patients with NAFLD using cardiac fat radiomics-based machine learning by Mengjie Liang, Liting Fang, Xie Chen, Wendi Huang

“…SHAP analysis revealed the importance of radiomics features from EAT and PAT, as well as clinical factors such as diabetes duration, global longitudinal strain (GLS), and low-density lipoprotein cholesterol (LDL-C), in detecting severe coronary artery stenosis. …”
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