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

“…Introduction Depression and anxiety are highly prevalent mental health conditions that significantly affect quality of life and cause societal burdens. However, their detection and diagnosis rates remain low owing to the limitations of the current screening methods. …”
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PRKDC regulates cGAMP to enhance immune response in lung cancer treatment by Zhanghao Huang, Zhanghao Huang, Zhanghao Huang, Runqi Huang, Runqi Huang, Runqi Huang, Jun Zhu, Jun Zhu, Youlang Zhou, Youlang Zhou, Jiahai Shi, Jiahai Shi

“…Additionally, macrophages and lung cancer cells were co-cultured, and macrophage polarization and apoptosis levels in the lung cancer cells were detected through flow cytometry. Protein levels were analyzed through western blotting and immunofluorescence. …”
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Development of an Internet of Things (IoT) embedded open-source gamma-ray detector using CMOS image sensor technology by D. L. Corzi, D. L. Corzi, J. Lipovetzky, J. Lipovetzky, J. Lipovetzky, M. Gómez Berisso, M. Gómez Berisso, M. Gómez Berisso

“…The detector uses simple, physics-based processing algorithms to allow for particle detection using CMOS image sensors on boards with limited processing capabilities. …”
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A stratified therapeutic model incorporated with studies on regulatory B cells for elderly patients with newly diagnosed multiple myeloma by Wenjiao Tang, Yan Li, Zhongqing Zou, Jian Cui, Fangfang Wang, Yuhuan Zheng, Li Hou, Ling Pan, Bing Xiang, Hong Chang, Li Zhang, Ting Niu

“…Methods In this open‐label, non‐interventional, prospective study in the real world, 159 newly diagnosed MM (NDMM) patients over 65 years old were sequentially recruited and bone marrow aspirates prior to treatment were obtained to detect the ratios of Bregs by flow cytometry. Results Based on the CEMM2021 model, 147 patients had received at least one cycle of induction therapy, including bortezomib/dexamethasone (Bd) (n = 80), lenalidomide/dexamethasone (Rd) (n = 27), Bd with a third agent X (Bd + X) (n = 27), and other regimens (n = 13). …”
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Novel CYCLIN‐O pathogenic variants in a patient presenting with bronchiectasis secondary to reduced generation of multiple motile cilia by Kim Hoong Yap, Albert Yick Hou Lim, Biju Thomas, Carine Bonnard, Emmanuelle Szenker‐Ravi, Yan Ling Chong, Sudipto Roy, Bruno Reversade

“…Heightened clinical suspicion and adherence to established diagnostic algorithms are essential for timely recognition of this entity.…”
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Compression rates of microbial genomes are associated with genome size and base composition by Jon Bohlin, John H.-O. Pettersson

“…For instance, strings that are not compressible are random and carry a low information potential while the opposite is true for highly compressible strings. …”
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FL-DBENet: Double-branch encoder network based on segment anything model for farmland segmentation of large very-high-resolution optical remote sensing images by W. Feng, F. Guan, C. Sun, W. Xu, W. Xu

“…Although deep learning algorithms have been extensively applied to farmland extraction, their performance remains limited due to the scarcity of labeled farmland samples and restricted generalization capabilities. …”
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Ultrasensitive Isomer Discrimination: A Joint Surface‐Enhanced Raman Scattering (SERS) Spectroscopy and Machine Learning Strategy by Verónica Montes‐García, Victor F. Martín, Manuel Obelleiro‐Liz, Ignacio Pérez‐Juste, Artur Ciesielski, Paolo Samorì

“…The integration of machine learning methodologies, such as Partial Least Squares Regression and Artificial Neural Networks, significantly enhances both quantitative analysis and classification accuracy, achieving detection limits as low as 2 × 10⁻⁸ m. Validation with commercially available ibuprofen samples shows excellent agreement with traditional circular dichroism results, highlighting the method's robustness and precision. …”
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Key Vital Signs Monitor Based on MIMO Radar by Michael Gottinger, Nicola Notari, Samuel Dutler, Samuel Kranz, Robin Vetsch, Tindaro Pittorino, Christoph Würsch, Guido Piai

“…Key vital parameters that can be measured in the second step are respiration rate, asynchronous respiratory movement of chest and abdomen and limb movements. The developed algorithms were tested through experiments. The achieved mean absolute error (MAE) for the locations of the xiphoid and navel was less than 5 cm and the categorical accuracy of pose classification and limb movement detection was better than 90% and 98.6%, respectively. …”
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Health system costs of providing outpatient care for diabetes in people with TB in the Philippines by T. Yamanaka, M.C. Castro, J.P. Ferrer, J.A. Solon, S.E. Cox, Y.V. Laurence, A. Vassall

“…RESULTS: The mean cost per service ranged from USD0.53 for DM risk assessment to USD23.72 for oral glucose tolerance test. The cost per case detected for different algorithms varied from USD17.43 to USD80.81. …”
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Innovative Expert-Based Tools for Spatiotemporal Shallow Landslides Mapping: Field Validation of the GOGIRA System and Ex-MAD Framework in Western Greece by Michele Licata, Francesco Seitone, Efthimios Karymbalis, Konstantinos Tsanakas, Giandomenico Fubelli

“…We tested an integrated approach combining the Ground Operative System for GIS Input Remote-data Acquisition (GOGIRA) with the Expert-based Multitemporal AI Detector (ExMAD). GOGIRA is a low-cost system for efficient georeferenced data collection, while ExMAD uses AI and multitemporal Sentinel-2 imagery to detect landslide triggering times. …”
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Targeted Sequencing of Lung Function Loci in Chronic Obstructive Pulmonary Disease Cases and Controls. by María Soler Artigas, Louise V Wain, Nick Shrine, Tricia M McKeever, UK BiLEVE, Ian Sayers, Ian P Hall, Martin D Tobin

“…For this reason we employed a rigorous quality control pipeline for variant detection which included the use of 3 independent calling algorithms. …”
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An Attention-based Model for Recognition of Facial Expressions Using CNN-BiLSTM by Sushil Kumar Singh, Manish Kumar, Ikram Majeed Khan, A. Jayanthiladevi, Chirag Agarwal

“…These issues often result in low accuracy, unreliable recognition rates, and slow convergence. …”
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Movement Disorders and Smart Wrist Devices: A Comprehensive Study by Andrea Caroppo, Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Pietro Aleardo Siciliano, Alessandro Leone

“…Moreover, some articles also reported the type of raw data extracted from the smart wrist device, the implemented designed algorithmic pipeline, and the data classification methodology. …”
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Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach by Yu Wang, Mudassar Ali, Tariq Mahmood, Amjad Rehman, Tanzila Saba

“…However, segmenting and classifying breast masses in mammograms is challenging due to their similar shapes to the surrounding glands. Current target detection algorithms have limited applications and low accuracy. …”
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Therapeutic Plasma Exchange in the Management of Postpartum HELLP Syndrome: A Case Report by Parul Jaiswal, Prashant Suryarao, Dipak Kolate

“…Haemolysis, Elevated Liver enzymes and Low Platelet count (HELLP) syndrome is a serious obstetric complication occurring during pregnancy or postpartum. …”
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Continual Learning With Neuromorphic Computing: Foundations, Methods, and Emerging Applications by Mishal Fatima Minhas, Rachmad Vidya Wicaksana Putra, Falah Awwad, Osman Hasan, Muhammad Shafique

“…., sparse spike-driven operations and bio-plausible learning rules) for improving energy efficiency and performance, thereby enabling efficient CL algorithms (e.g., unsupervised learning approach) executed in dynamically-changed environments with resource-constrained computing systems. …”
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Classification of Individuals With COVID-19 and Post–COVID-19 Condition and Healthy Controls Using Heart Rate Variability: Machine Learning Study With a Near–Real-Time Monitoring C... by Carlos Alberto Sanches, Andre Felipe Henriques Librantz, Luciana Maria Malosá Sampaio, Peterson Adriano Belan

“…Classification models were developed using supervised machine learning algorithms (decision tree, support vector machines, k-nearest neighbor, and neural networks) and evaluated through cross-validation. …”
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Provenance-Finding of Dust Storms Using AVHRR Sensor Images of NOAA Satellite (Case Study: Southwest of Iran) by Mohammad Hossein Rezaei Moghaddam, Mojtaba Mahdian Boruojeni

“…After preparing the images, in the processing stage, the particles were identified by applying the dust detection algorithms including brightness temperature differences in the thermal infrared bands (band 4&5 AVHRR sensor) and false color combination (R: 1 G: 2 B4). 3- Results and Discussion Detecting the images, a total of 62 origin points were extracted in the southwest of the country which were transferred to the GIS environment. …”
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AI and Machine Learning in V2G technology: A review of bi-directional converters, charging systems, and control strategies for smart grid integration by Nagarajan Munusamy, Indragandhi Vairavasundaram

“…AI-powered predictive analytics can forecast energy demand and supply, enabling proactive charging and discharging strategies. ML algorithms can optimize charging rates, battery health, and grid stability while also detecting anomalies and preventing potential faults. …”
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