Deep Learning for Medical Image Analysis Applications in Disease Detection and Diagnosis by Panchadhyayee Swagata, N Shirisha, S Sureshkumar, Priya S Harthy Ruby, Ramalingam Vanaja, M Mahima

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Advanced intrusion detection technique (AIDT) for secure communication among devices in internet of medical things (IoMT) by M. Ramya, Pradeep Sudhakaran, Yuvaraj Sivagnanam, C. Santhana Krishnan

“…Considering the aforementioned, this study suggests an advanced intrusion detection technology (AIDT) to guarantee safe data exchange amongst IoMT devices. …”
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A Multifeature Fusion Network for Tree Species Classification Based on Ground-Based LiDAR Data by Yaoting Liu, Yiming Chen, Zhengjun Liu, Jianchang Chen, Yuxuan Liu

“…Light detection and ranging (LiDAR) holds considerable promise for tree species classification. …”
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OCRClassifier: integrating statistical control chart into machine learning framework for better detecting open chromatin regions by Xin Lai, Xin Lai, Min Liu, Yuqian Liu, Xiaoyan Zhu, Jiayin Wang, Jiayin Wang

“…In recent years, there has been a growing interest in using plasma cell-free DNA (cfDNA) sequencing data to detect OCRs. By analyzing the characteristics of cfDNA fragments and their sequencing coverage, researchers can differentiate OCRs from non-OCRs. …”
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System analysis and information processing to solve the problem of detecting breakdowns of computer information storage by N. M. Kodatsky, E. A. Revyakina, A. R. Gazizov

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Infra-3DRC-FusionNet: Deep Fusion of Roadside Mounted RGB Mono Camera and Three-Dimensional Automotive Radar for Traffic User Detection by Shiva Agrawal, Savankumar Bhanderi, Gordon Elger

“…Mono RGB cameras and automotive radar sensors provide a complementary information set that makes them excellent candidates for sensor data fusion to obtain robust traffic user detection. …”
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Detection of Potentially Anomalous Cosmic Particle Tracks Acquired with CMOS Sensors: Validation of Rough k–Means Clustering with PCA Feature Extraction by Hachaj Tomasz, Piekarczyk Marcin, Wąs Jarosław

“…We plan to deploy the presented methodology in the image processing pipeline of the large data set we are working on in the CREDO project. …”
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Hierarchical RUL Prediction for Turbofan Engines Based on Health Stage Classification and Change Point-Guided Data Augmentation by Kiymet Ensarioglu

“…This method segments the dataset into pre- and post-change intervals and applies data augmentation both to simulate the truncated nature of the test data—where engines are monitored up to unknown failure points—and to construct a balanced training set that fairly represents both healthy and degraded conditions, thereby improving the robustness and generalization of the classification model. …”
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Clinical Significance of Perioperative Minimal Residual Disease Detected by Circulating Tumor DNA in Patients With Lung Cancer With a Long Follow-up Data: An Exploratory Study by Shuta Ohara, MD, PhD, Kenichi Suda, MD, PhD, Sumedha Sudhaman, PhD, Akira Hamada, MD, PhD, Masato Chiba, MD, PhD, Masaki Shimoji, MD, PhD, Toshiki Takemoto, MD, PhD, Ekaterina Kalashnikova, PhD, Samantha K. Cheung, PhD, Michael Krainock, MD, PhD, Jordan Feeney, BS, Himanshu Sethi, MPH, Minetta C. Liu, MD, Junichi Soh, MD, PhD, Yasuhiro Tsutani, MD, PhD, Tetsuya Mitsudomi, MD, PhD

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KRID: A Large-Scale Nationwide Korean Road Infrastructure Dataset for Comprehensive Road Facility Recognition by Hyeongbok Kim, Eunbi Kim, Sanghoon Ahn, Beomjin Kim, Sung Jin Kim, Tae Kyung Sung, Lingling Zhao, Xiaohong Su, Gilmu Dong

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Refined Monitoring of Water Bodies in Built-Up Areas and Analysis and Evaluation of Water Color Characteristics in Complex Urban Backgrounds by Bin Li, Yong Xie, Zui Tao, Wen Shao, Gan Qin

“…Water body extraction in complex urban settings is susceptible to environmental disturbances, reducing monitoring accuracy and efficiency. …”
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Towards zero-shot learning in 3D change detection: improving generalization with custom augmentations and evaluation by Riccardo Contu, Valerio Marsocci, Virginia Coletta, Roberta Ravanelli, Simone Scardapane

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Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

“…Abstract Diabetes Mellitus (DM) is a global health challenge, and accurate early detection is critical for effective management. The study explores the potential of machine learning for improved diabetes prediction using microarray gene expression data and PIMA data set. …”
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Smartphone sensor-based depression detection in campus environments: a proof-of-concept study with small-sample behavioral analysis by Yichen Bai, Yueze Liu, Yang Zhang, Amr Tolba

“…IntroductionDepression is a rising global health issue, particularly among adolescents, with university students facing distinct mental health challenges.MethodsThis proof-of-concept study explores smartphone sensor-based depression detection in Chinese university campus settings using a small sample of 12 participants. …”
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Optimal selection of diagnostic method for diabetes mellitus using complex bipolar fuzzy dynamic data by Hanan Alolaiyan, Maryam Liaqat, Abdul Razaq, Umer Shuaib, Abdul Wakil Baidar, Qin Xin

“…We formulate a modified score function to address the shortcomings of the current score function in the CBF settings. Furthermore, we employ these operators to offer a systematic technique to tackle multiple attribute decision-making (MADM) problems using CBF data. …”
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High Spatiotemporal Resolution River Networks Mapping on Catchment Scale Using Satellite Remote Sensing Imagery and DEM Data by Peng Li, Yun Zhang, Cunren Liang, Houjie Wang, Zhenhong Li

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Trigger tools in healthcare settings: insights from an umbrella review by Mohammed As'ad, Nawarh Faran, Awad Al Omari

“…Results showed substantial variation in trigger tool performance. Detection rates ranged from 0.8% to 66% across healthcare settings and populations. …”
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Fast SVM-based Multiclass Classification in Large Training Sets by M. Yu. Kurbakov, V. V. Sulimova

“…Experimental investigation of proposed methods was made on three large handwritten digit images data sets of different size and one large intrusion detection data set. …”
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First recorded isolation of Mycobacterium kansasii in a nonendemic setting by Jana Dajani, MD, Ali Shakhshir, MD, Ayham Sawalmeh, MD, Ameer Awashra, MD, Mo'tasem Dweekat, MD, Khaled Al-ali, MD, Ahmad Mohammad Adnan fatayer, MD

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MyμAlbumin: A Cutting-Edge Immunoturbidity-Based Device with Real-Time and Seamless Data Transmission for Early Detection of Chronic Kidney Disease at the Point of Care by Wanna Chaijaroenkul, Napaporn Youngvises, Artitaya Thiengsusuk, Tullayakorn Plengsuriyakarn, Jakkrapong Suwanboriboon, Kridsada Sirisabhabhorn, Wanchai Meesiri, Kesara Na-Bangchang

“…Additionally, the device supports real-time, seamless data transmission, making it ideal for integration into remote healthcare settings.…”
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