Grey wolf optimization technique with U-shaped and capsule networks-A novel framework for glaucoma diagnosis by Govindharaj I, Ramesh T, Poongodai A, Senthilkumar K. P, Udayasankaran P, Ravichandran S

“…The glaucoma classification depends on CapsNet as a deep learning model that provides exceptional image detection to ensure precise diagnosis. …”
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An automatic approach to detect skin cancer utilizing active infrared thermography by Ricardo F. Soto, Sebastián E. Godoy

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A procalcitonin-based algorithm to guide antibiotic therapy in secondary peritonitis following emergency surgery: a prospective study with propensity score matching analysis. by Ting-Shuo Huang, Shie-Shian Huang, Yu-Chiau Shyu, Chun-Hui Lee, Shyh-Chuan Jwo, Pei-Jer Chen, Huang-Yang Chen

“…Multivariate-adjusted extended Cox model demonstrated that the PCT-based algorithm was significantly associated with a 87% reduction in hazard of antibiotic exposure within 7 days (hazard ratio [HR] 0.13, 95% CI 0.07-0.21, p < 0.001), and a 68% reduction in hazard after 7 days (adjusted HR 0.32, 95% CI 0.11-0.99, p  =  0.047). …”
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Applications and advances of multi-omics technologies in gastrointestinal tumors by Yuqing Liu, Feng Gao, Yang Cheng, Liang Qi, Haining Yu

“…However, challenges such as data heterogeneity, insufficient algorithm generalization, and high costs limit clinical translation. …”
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Parameter Optimization of a Bi-copter Type Unmanned Aerial Vehicle to Avoid Propeller-induced Vibrations During Hovering by Mehmet Kursat Yalcın, İlyas Kacar, Halil Bahadır Akyıldız

“…It is not seen significant differences on results from screening and genetic algorithm methods. Correlations between frequencies and structural responses are determined. …”
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基于脑影像及临床特征的机器学习模型预测缺血性卒中后心房颤动 A Machine Learning Model Based on Brain Imaging and Clinical Features for Predicting Atrial Fibrillation Detected after Stroke... by 张栗源1，刘涛2，姜勇1，李子孝1，3，王拥军1，3，杨晓萌1，3(ZHANG Liyuan1, LIU Tao2, JIANG Yong1, LI Zixiao1,3, WANG Yongjun1,3, YANG Xiaomeng1,3 )

“…After retaining independent features, the least absolute shrinkage and selection operator (LASSO) regression algorithm was used for feature selection and to construct a joint prediction model. …”
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Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants by Hanieh Talebi, Seyed Alireza Dastgheib, Maryam Vafapour, Reza Bahrami, Mohammad Golshan-Tafti, Mahsa Danaei, Sepideh Azizi, Amirhossein Shahbazi, Melina Pourkazemi, Maryam Yeganegi, Amirmasoud Shiri, Ali Masoudi, Heewa Rashnavadi, Hossein Neamatzadeh

“…For nRDS, biomarkers such as the lecithin/sphingomyelin (L/S) ratio and oxidative stress indicators have been effectively used in innovative diagnostic methods, including attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and high-content screening for ABCA3 modulation. Machine learning algorithms like Partial Least Squares Regression (PLSR) and C5.0 have shown potential in accurately identifying critical health indicators. …”
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Rapid differentiation of patients with lung cancers from benign lung nodule based on dried serum Fourier-transform infrared spectroscopy combined with machine learning algorithms by Huanyu Li, Lixue Dai, Shaomei Guo, Hongluan Wang, Lei Lei, Jie Yu, Xiaoyun Li, Jun Wang

“…While low-dose computed tomography (LDCT) screening enables earlier detection, its high false-positive rate, primarily due to benign lung nodules (BLN), necessitates more accurate diagnostic tools. …”
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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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Old Drugs, New Indications (Review) by I. I. Miroshnichenko, E. A. Valdman, I. I. Kuz'min

“…A targeted search for the possibility of repurposing drugs using an automatic procedure is being carried out, where a large number of chemical compounds are tested for activity or affinity for receptors and enzymes – high-throughput screening. Computer design has become widespread, which or repurposing "in silico", where information about the drug is used: targets, chemical structures, metabolic pathways, side effects, followed by the construction of appropriate models. …”
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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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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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Identification of potential biomarkers for 2022 Mpox virus infection: a transcriptomic network analysis and machine learning approach by Joy Prokash Debnath, Kabir Hossen, Sabrina Bintay Sayed, Md. Sayeam Khandaker, Preonath Chondrow Dev, Saifuddin Sarker, Tanvir Hossain

“…Intriguingly, 13 key DEGs were identified across hubs and clusters, highlighting their aberrant expressions in cell cycle regulation, immune responses, and cancer pathways. Biomarker screening via Random Forest (RF) model (selected with PyCaret from multiple models) and validation through t-distributed stochastic neighbor embedding (t-SNE) algorithm, principal component analysis (PCA), and ROC curve analysis employing Logistic Regression and Random Forest, identified 6 key DEGs (TXNRD1, CCNB1, BUB1, CDC20, BUB1B, and CCNA2) as promising biomarkers (AUC > 0.7) for clade IIb infection. …”
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Design of public space guide system based on augmented reality technology by Pu Jiao, Limin Ran

“…The research is based on imaging techniques using augmented reality technology and camera image capture. Then, it uses screen error algorithms and scale-invariant feature transformation operators to test the quality of scene spatial models. …”
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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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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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A Web-Based Interface That Leverages Machine Learning to Assess an Individual&#x2019;s Vulnerability to Brain Stroke by Divyansh Bhandari, Arnav Agarwal, R. Reena Roy, Rajaram Priyatharshini, Rodriguez Rivero Cristian

“…We compare a range of algorithms-including traditional classifiers and deep learning models-and report comprehensive performance metrics (accuracy, precision, recall, F1-score, and AUC-ROC) for each. …”
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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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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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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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