River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Building upon this foundation, we introduce the LR-DETR, a lightweight evolution of RT-DETR for river floating object detection. This model incorporates the High-level Screening-feature Path Aggregation Network (HS-PAN), which refines feature fusion through a novel bottom-up fusion path, significantly enhancing its expressive power. …”
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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by S. Ajith, S. Vijayakumar, N. Elakkiya

“…Artificial intelligence integration into foodgrain quality assessment leverages hyperspectral imaging and predictive models to enhance grading, adulteration detection, and contaminant screening, contributing to food safety and market competitiveness. …”
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Identification of Mattic Epipedon Degradation on the Northeastern Qinghai–Tibetan Plateau Using Hyperspectral Data by Junjun Zhi, Hong Zhu, Jingwen Yang, Qiuchen Yan, Dandan Zhi, Zhongbao Sun, Liangwei Ge, Chengwen Lv

“…This study aimed to clarify the hyperspectral response mechanisms of mattic epipedon degradation and, based on hyperspectral technology, to construct models for identifying degraded mattic epipedon and screen preprocessing methods suitable for different moisture conditions. …”
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Predicting the generalization of computer aided detection (CADe) models for colonoscopy by Joel Shor, Carson McNeil, Yotam Intrator, Joseph R. Ledsam, Hiro-o Yamano, Daisuke Tsurumaru, Hiroki Kayama, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg

“…Abstract Generalizability of AI colonoscopy algorithms is important for wider adoption in clinical practice. …”
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Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnex... by Lu Liu, Wenjun Cai, Feibo Zheng, Hongyan Tian, Yanping Li, Ting Wang, Xiaonan Chen, Wenjing Zhu

“…Critical relevance statement The ultrasound radiomics-based machine learning model holds the potential to elevate the professional ability of less-experienced radiologists and can be used to assist in the clinical screening of ovarian cancer. …”
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A Novel Model for Noninvasive Haemoglobin Detection Based on Visibility Network and Clustering Network for Multi-Wavelength PPG Signals by Lei Liu, Ziyi Wang, Xiaohan Zhang, Yan Zhuang, Yongbo Liang

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Can artificial intelligence and contrast-enhanced mammography be of value in the assessment and characterization of breast lesions? by Lamiaa Mohamed Bassam Hashem, Heba Monir Azzam, Ghadeer Saad Abd El-Shakour El-Gamal, MennatAllah Mohamed Hanafy

“…Radiologists, under heavy and prolonged workloads, are more prone to errors and to reduce such mistakes, and computer-aided diagnosis (CAD) has been introduced. …”
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Machine Learning-Based Interpretable Screening for Osteoporosis in Tuberculosis Spondylitis Patients Using Blood Test Data: Development and External Validation of a Novel Web-Based... by Yasin P, Ding L, Mamat M, Guo W, Song X

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Applications of AI-Based Models for Online Fraud Detection and Analysis by Antonis Papasavva, Samantha Lundrigan, Ed Lowther, Shane Johnson, Enrico Mariconti, Anna Markovska, Nilufer Tuptuk

“…Results We discuss the state-of-the-art AI and NLP techniques used to analyse various online fraud categories; the data sources used for training the AI and NLP models; the AI and NLP algorithms and models built; and the performance metrics employed for model evaluation. …”
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Enhancing Fracture Detection in Remote Settings: Evaluating the Efficacy of FIXUS AI Deep Learning Algorithms in Identifying Fifth Metatarsal Fractures Using Mixed-Quality X-rays by Atta Taseh MD, Alireza Gholipour PhD, Mani Eftekhari, Alireza Ebrahimi MD, Alexandra F. Flaherty MD, MS, Alexandra F. Flaherty MD, MS, Sumner Jones, Varun Nukala, Gregory R. Waryasz MD, Daniel Guss MD, MBA, John Y. Kwon MD, Christopher W. DiGiovanni MD, Lorena Bejarano-Pineda MD, Soheil Ashkani-Esfahani MD

“…This emphasizes the need for training algorithms on images of varying quality to create more generalizable models capable of operating effectively across diverse settings.…”
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Numerical Background-Oriented Schlieren for Phase Reconstruction and Its Potential Applications by Shiwei Liu, Yichong Ren, Haiping Mei, Zhiwei Tao, Shuran Ye, Xiaoxuan Ma, Ruizhong Rao

“…This framework integrates two stages: forward modeling, using ray tracing to simulate image degradation, and inverse processing, using optical flow and a conjugate gradient algorithm to extract displacements and reconstruct phase information. …”
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A diagnostic model for polycystic ovary syndrome based on machine learning by Cheng Tong, Yue Wu, Zhenchao Zhuang, Ying Yu

“…The data of 10 case groups and 10 control groups were randomly selected as validation set data, and the rest of the data were included in the model construction. The acquired data were screened for variables, a classification model based on a machine learning algorithm was constructed, and the constructed model was evaluated and validated for diagnostic efficacy. …”
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Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…Compared with previous studies, a more stable water content prediction model of Anshan magnetite was constructed by combining data preprocessing, CARS feature screening and nonlinear regression algorithm, which provides higher precision support for water content detection in mining production.…”
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Model of a Novel PCB Coil for High-Sensitivity Metal Detector by Han Zhang, Mingxing Song, Yuejiu Zhu, Xianze Xu, Fengqiu Xu

“…An optimization problem is constructed from the numerical model, and the optimal design parameters of the receiving coil are determined via a heuristic algorithm. …”
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Study on the Impact of Input Parameters on Seawater Dissolved Oxygen Prediction Models by Wenqing Li, Jing Lv, Yuhang Wang, Xiangfeng Kong

“…Future research will develop a parameter adaptive selection algorithm, conduct the dynamic monitoring of multi-scale environmental factors, and achieve the intelligent optimization and verification of model parameters.…”
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Self‐Learning e‐Skin Respirometer for Pulmonary Disease Detection by Anand Babu, Getnet Kassahun, Isabelle Dufour, Dipankar Mandal, Damien Thuau

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A Convolutional Neural Network Using Anterior Segment Photos for Infectious Keratitis Identification by Satitpitakul V, Puangsricharern A, Yuktiratna S, Jaisarn Y, Sangsao K, Puangsricharern V, Kasetsuwan N, Reinprayoon U, Kittipibul T

“…Our models can be used as a screening tool for non-ophthalmic health care providers and ophthalmologists for rapid provisional diagnosis of infectious keratitis.Keywords: infectious keratitis, cornea ulcer, keratitis, conventional neural network, deep learning algorithm…”
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Development and Validation of Early Alert Model for Diabetes Mellitus–Tuberculosis Comorbidity by Zhaoyang Ye, Guangliang Bai, Ling Yang, Li Zhuang, Linsheng Li, Yufeng Li, Ruizi Ni, Yajing An, Liang Wang, Wenping Gong

“…This study identified three potential immune-related biomarkers for DM–TB, and the constructed risk assessment model demonstrated significant predictive efficiency, providing an early screening strategy for DM–TB.…”
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Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic... by Jimmy Londono, Shohreh Ghasemi, Altaf Hussain Shah, Amir Fahimipour, Niloofar Ghadimi, Sara Hashemi, Zohaib Khurshid, Mahmood Dashti

“…Machine learning (ML) algorithms have been used to accurately identify cephalometric landmarks and detect irregularities related to orthodontics and dentistry. …”
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SIGLEC1 has the potential to be an immune-related prognostic indicator in colon adenocarcinoma: a study based on transcriptomic data and Mendelian randomization analysis by Jue Gu, Yaxuan Wang, Hui Zhang, Haijuan Gu, Haixia Zhu

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