Applying Neural Networks to Analyse Inflammatory, Sociodemographic, and Psychological Factors in Non-Melanoma Skin Cancer and Colon Cancer: A Statistical and Artificial Intelligenc... by Răzvan Mercuţ, Marius Eugen Ciurea, Emil Tiberius Traşcă, Mihaela Ionescu, Maria Filoftea Mercuţ, Patricia Mihaela Rădulescu, Cristina Călăraşu, Liliana Streba, Alin Gabriel Ionescu, Dumitru Rădulescu

“…Advanced neural network algorithms were employed to detect subtle patterns and interactions among these factors. …”
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Updates on WHO 5th edition classification, molecular characteristics and tumor microenvironment of adrenocortical carcinomas by Yuto Yamazaki, Yuta Tezuka, Yoshikiyo Ono, Fumitoshi Satoh, Hironobu Sasano, Takashi Suzuki

“…The recently published WHO 5th edition “Endocrine and Neuroendocrine Tumours” recommends a diagnostic algorithm employing not only one but several proposed histopathological criteria—including the Weiss criteria and its revision and the Helsinki criteria—in addition to the Reticulin algorithm, the Ki-67 proliferative index, and others depending upon their histopathological features. …”
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Classification and Time-Frequency Localization of Arbitrary LPWAN Signals With Radial Deformable DETR by Chun Ho Kong, Haibo Hu

“…This paper proposes to classify and localize time-frequency locations of LPWAN signals by an enhanced version of Deformable DEtection TRansformer (Deformable DETR). We devise an attention radius suitable for processing Low Power Wide Area Network (LPWAN) Spectrogram traces extracted from Software Defined Radios (SDRs) IQ data with Short-Time Fourier Transform (STFT). …”
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Enhancing Crop Health: Advanced Machine Learning Techniques for Prediction Disease in Palm Oil Tree by Nandy Manish, Kumar Yalakala Dinesh

“…Palm oil trees are one of the key crops in the world's agricultural economy yet they are vulnerable to a number of diseases which can reduce yields substantially. Currently disease detection and management is usually labor intensive and slow, thus delays in detection and response and increased losses in yields. …”
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Relationship between depression and coronary artery disease in an open female and male population of a middle-urbanized city of Western Siberia by E. V. Akimova, V. V. Gafarov, E. I. Gakova, A. M. Akimov, M. M. Kayumova

“…The severity of depression was assessed as low, moderate, and high. On the basis of the algorithm, the levels of depression were established: low and moderate levels — no sign, high level — presence of a sign.Results. …”
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Microcontroller-Based Platform for Lithium-Ion Battery Charging and Experimental Evaluation of Charging Strategies by Laurentiu Marius Baicu, Mihaela Andrei, Bogdan Dumitrascu

“…The system successfully regulated current and voltage, managed preconditioning for low-voltage cells, and transitioned smoothly between charging phases. …”
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Time-series high spatio-temporal resolution vegetation leaf area index estimation based on NDVI trends by Chen Li, Hongmin Zhou, Jia Tang, Changjing Wang, Ziyu Wang, Jinlin Qi, Bihong Yang, Ruojing Fang

“…However, due to limitations of recent satellite observations and retrieval algorithms, the prevailing operational LAI product is of low spatial resolution, which is insufficient to support fine-scale detection of land surface vegetation changes. …”
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Robust Fault Classification in Permanent Magnet Synchronous Machines Under Dynamic and Noisy Conditions by Mikal Laursen, Van-Van Huynh, Duy-Hung Ha, Mahmoud S. Mahmoud, van Khang Huynh

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A New Method for Weak Fault Feature Extraction Based on Improved MED by Junlin Li, Jingsheng Jiang, Xiaohong Fan, Huaqing Wang, Liuyang Song, Wenbin Liu, Jianfeng Yang, Liangchao Chen

“…Because of the characteristics of weak signal and strong noise, the low-speed vibration signal fault feature extraction has been a hot spot and difficult problem in the field of equipment fault diagnosis. …”
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Long-Distance Measurements Using a Chromatic Confocal Sensor by Kiril Ivanov Kurtev, Juan Manuel Trujillo-Sevilla, José Manuel Rodríguez-Ramos

“…In addition, the superiority of low-pass filtering over Gaussian fitting over the detected spectrum is shown.…”
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Real-Time Acoustic Measurement System for Cutting-Tool Analysis During Stainless Steel Machining by Tom Salm, Kourosh Tatar, José Chilo

“…Using the TreeBagger machine-learning algorithm, the system accurately predicts tool wear, detecting both gradual and abrupt wear patterns. …”
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Artificial intelligence based vision transformer application for grading histopathological images of oral epithelial dysplasia: a step towards AI-driven diagnosis by Mahdi Hadilou, Nazanin Mahdavi, Elham Keykha, Ali Ghofrani, Elahe Tahmasebi, Masoud Arabfard

“…Results Image preprocessing yielded 2,545 low-risk, 2,054 high-risk, 726 mild, 831 moderate, 449 severe, and 937 normal tissue patches. …”
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Future projection of East Asian atmospheric rivers in high-resolution climate models by Yeeun Kwon, Seok-Woo Son

“…ARs are also projected to become more intense and persistent with a considerable increase in extreme precipitation, although the quantitative change slightly differs depending on the AR detection algorithms. Such changes are primarily driven by thermodynamic processes, with dynamic processes playing a secondary role. …”
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Integrated Ultrasound‐Enrichment and Machine Learning in Colorimetric Lateral Flow Assay for Accurate and Sensitive Clinical Alzheimer's Biomarker Diagnosis by Shuqing Wang, Yan Zhu, Zhongzeng Zhou, Yong Luo, Yan Huang, Yibiao Liu, Tailin Xu

“…Abstract The colloidal gold nanoparticle (AuNP)‐based colorimetric lateral flow assay (LFA) is one of the most promising analytical tools for point‐of‐care disease diagnosis. However, the low sensitivity and insufficient accuracy still limit its clinical application. …”
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Effectiveness of biomarker-guided duration of antibiotic treatment in children hospitalised with confirmed or suspected bacterial infection: the BATCH RCT by Cherry-Ann Waldron, Philip Pallmann, Simon Schoenbuchner, Debbie Harris, Lucy Brookes-Howell, Céu Mateus, Jolanta Bernatoniene, Katrina Cathie, Saul N Faust, Josie Henley, Lucy Hinds, Kerry Hood, Chao Huang, Sarah Jones, Sarah Kotecha, Sarah Milosevic, Helen Nabwera, Sanjay Patel, Stéphane Paulus, Colin VE Powell, Jenny Preston, Huasheng Xiang, Emma Thomas-Jones, Enitan D Carrol

“…HCPs took a while to become familiar with the intervention algorithm, and as the intervention test did not align with the clinical pathway, often there were delays in getting the PCT results, which meant that adherence to the algorithm was low. …”
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Validation of Replicable Pipeline 3D Surface Reconstruction for Patient-Specific Abdominal Aortic Lumen Diagnostics by Edoardo Ugolini, Giorgio La Civita, Moad Al Aidroos, Samuele Salti, Giuseppe Lisanti, Emanuele Ghedini, Gianluca Faggioli, Mauro Gargiulo, Giovanni Rossi

“…<b>Conclusions:</b> The proposed algorithm can correctly reconstruct pathological vessels. …”
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Defining Seropositivity Thresholds for Use in Trachoma Elimination Studies. by Stephanie J Migchelsen, Diana L Martin, Khamphoua Southisombath, Patrick Turyaguma, Anne Heggen, Peter Paul Rubangakene, Hassan Joof, Pateh Makalo, Gretchen Cooley, Sarah Gwyn, Anthony W Solomon, Martin J Holland, Paul Courtright, Rebecca Willis, Neal D E Alexander, David C W Mabey, Chrissy H Roberts

“…The expectation-maximisation algorithm estimated seroprevalence at 10.4% (Laos), 24.3% (Uganda) and 29.3% (The Gambia). …”
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Machine Learning to Assess Relatedness: The Advantage of Using Firm-Level Data by Giambattista Albora, Andrea Zaccaria

“…In this work, we compare networks and machine learning algorithms trained not only on country-level data, but also on firms, which is something not much studied due to the low availability of firm-level data. …”
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A Machine Learning Based Framework for a Stage-Wise Classification of Date Palm White Scale Disease by Abdelaaziz Hessane, Ahmed El Youssefi, Yousef Farhaoui, Badraddine Aghoutane, Fatima Amounas

“…To classify the WSD into its four classes (healthy, low infestation degree, medium infestation degree, and high infestation degree), two types of ML algorithms were tested; classical machine learning methods, namely, support vector machine (SVM) and k-nearest neighbors (KNN), and ensemble learning methods such as random forest (RF) and light gradient boosting machine (LightGBM). …”
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Efficient Identification and Classification of Pear Varieties Based on Leaf Appearance with YOLOv10 Model by Niman Li, Yongqing Wu, Zhengyu Jiang, Yulu Mou, Xiaohao Ji, Hongliang Huo, Xingguang Dong

“…Compared with existing recognition networks and target detection algorithms such as YOLOv7, ResNet50, VGG16, and Swin Transformer, YOLOv10 performs the best in pear leaf recognition in natural scenes. …”
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