Monte Carlo Simulation Approach to Calculate Value at Risk: Application to WIG20 and mWIG40 by Aleksandra Helena Pasieczna

“…Our approach involves obtaining Monte Carlo parameters by fitting real historical data of different periods to probability distributions. We applied the algorithm to the WIG20 and mWIG40 stock indices, and performed simulations for the Value at Risk at 95% and 99% confidence intervals over six estimation periods ranging from 1 trading day to 250 trading days. …”
Get full text

Normalization of Multifocal Acoustic Radiation Force Impulse Images by Nuria GONZÁLEZ-SALIDO, Jorge CAMACHO

“…Performance of the proposed algorithm is experimentally evaluated with tissue mimicking phantoms.…”
Get full text

Engineered feature embeddings meet deep learning: A novel strategy to improve bone marrow cell classification and model transparency by Jonathan Tarquino, Jhonathan Rodríguez, David Becerra, Lucia Roa-Peña, Eduardo Romero

“…Cytomorphology evaluation of bone marrow cell is the initial step to diagnose different hematological diseases. …”
Get full text

Decentralized coordinated emergency frequency control strategy for renewables-rich power systems based on multi-agent reinforcement learning by Zhenglong Sun, Junpeng Han, Weihan Chen, Rui Zhang, Yong Liu, Yoash Levron, Juri Belikov

“…Combined with the system frequency response (SFR) model parameter identification method, the grid frequency regulation capability of different fault conditions is evaluated. A MADRL algorithm with integrated SFR model is developed to overcome the problem of inaccurate assessment of centralized action values in the MADRL algorithm used for EFC, and a decentralized and cooperative EFC strategy is realized. …”
Get full text

Uso de Métodos Monte Carlo na Modelagem de Fontes Radioativas Naturais by Gutemberg Luiz Sales Claudino, José Vieira, Viriato Leal Neto, Fernando Lima, José Santos

“…To perform the simulations was adapted MCE MSTA, composed by phantom MASH (Male Adult meSH) in orthostatic position coupled to EGSnrc, with the algorithm of FDP NT allowing execution for different values of rmax. …”
Get full text

From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy by Rafael Herschberg, Lisa Rateau, Laure Martinelli, Fanny Balbaud-Célérier, Jean Dhers, Anna Fraczkiewicz, Gérard Ramstein, Franck Tancret

“…A pairwise comparison algorithm is used to assess a particular property among a group of different alloys tested simultaneously in identical conditions. …”
Get full text

Optimizing XGBoost Hyperparameters for Credit Scoring Classification Using Weighted Cognitive Avoidance Particle Swarm by Atul Vikas Lakra, Sudarson Jena, Kaushik Mishra

“…The proposed WCAPSO-XGB model tunes the hyperparameters of XGBoost and classifies the credit scoring, and the experimental results are compared with various classifier such as Random Forest (RF), K-neighbors (KNN), Gaussian Naive Bayes (NB), AdaBoost, Gradient Boosting, Logistic Regression (LR), Neural Network (NN), Decision Tree (DT) and Linear Discriminant Analysis (LDA), and hyperparameter optimization methods, such as Grid Search (GS), Random Search (RS), Bays Optimization, Optuna Optimization, Hybrid Snake Optimizer Algorithm (HSOA), Exploratory Cuckoo Search, island Cuckoo Search (iCSPM and iCSPM2), and Improved SSA (ISSA) with HDPM, on four different datasets with a varying number of instances from small to large. …”
Get full text

Risk factors and an interpretability tool of in-hospital mortality in critically ill patients with acute myocardial infarction by Rui Yang, Tao Huang, Renqi Yao, Di Wang, Yang Hu, Longbing Ren, Shaojie Li, Yali Zhao, Zhijun Dai

“…Conclusion: We built the BRF model and the web-based tool by the model algorithm. The model effect has been verified externally. …”
Get full text

Comparing and Combining Artificial Intelligence and Spectral/Statistical Approaches for Elevating Prostate Cancer Assessment in a Biparametric MRI: A Pilot Study by Rulon Mayer, Yuan Yuan, Jayaram Udupa, Baris Turkbey, Peter Choyke, Dong Han, Haibo Lin, Charles B. Simone

“…Recently, a different spectral/statistical approach has been used to successfully evaluate spatially registered biparametric MRIs for prostate cancer. …”
Get full text

Initial experience of parenchyma-sparing liver resection with systematic selective hepatic vein reconstruction for colorectal metastases by Yevhenii Trehub, Åsmund Avdem Fretland, Artem Zelinskyi, Dzmitrii Kharkov, Oleksii Babashev, Dmytro Chieverdiuk, Artem Shchebetun, Kyrylo Khyzhniak, Maksym Pavlovskii, Andrii Strokan, Sergii Zemskov

“…Objectives This study aims to assess the feasibility and short-term and intermediate-term technical success rate of the concept of systematic selective hepatic vein (HV) reconstruction for parenchyma-sparing hepatectomies (PSHs) in patients with colorectal liver metastases (CRLM) in accordance with stage 2a of the IDEAL framework.Design The prospective case series of patients deemed eligible and operated on according to the concept.Setting All patients were treated by a single surgical team in three hospitals in Ukraine from June 2022 to November 2023.Participants The study included nine cases of resectable CRLM with at least one lesion located in the hepatocaval confluence with HV(s) invasion, for whom reconstruction of the HV(s) allowed for additional parenchyma preservation, being an alternative to major or extended hepatectomy.Interventions Liver resections with different types of HVs reconstruction (primary closure, patching, end-to-end anastomosis with or without grafting) were performed after a thorough evaluation of the future liver remnant volume, volume of potentially additionally preserved parenchyma and possibility of future repeat hepatectomies.Main outcome measures Postoperative morbidity, short-term and long-term patency of the reconstructed vessels, and the volume of additionally preserved parenchyma were the focus.Results Segmental resection was performed in four cases, two with graft interposition. …”
Get full text

Sustainable analysis of COVID-19 Co-packaged paxlovid: exploring advanced sampling techniques and multivariate processing tools by Shymaa S. Soliman, Nisreen F Abo- Talib, Mohamed R. Elghobashy, Mona A. Abdel Rahman

“…During the current study, a pioneering statistical technique namely, Latin Hypercube Sampling (LHS) was integrated with different multivariate chemometric models namely; Partial Least Squares (PLS), Genetic Algorithm‑Partial Least Squares (GA-PLS), Artificial Neural Networks (ANN), and Multivariate Curve Resolution‑Alternating Least Squares (MCR-ALS). …”
Get full text

The application of artificial intelligence models in predicting the risk of diabetic foot: a multicenter study by Yao Li, Siyuan Zhou, Bichen Ren, Shuai Ju, Xiaoyan Li, Wenqiang Li, Bingzhe Li, Yunmin Cai, Chunlei Chang, Lihong Huang, Zhihui Dong

“…Future work will focus on algorithm optimization, expanded datasets, and real-time monitoring integration to enable more precise, dynamic risk evaluation for improved DF prevention and early intervention.…”
Get full text

Machine learning modeling for the risk of acute kidney injury in inpatients receiving amikacin and etimicin by Pei Zhang, Qiong Chen, Jiahui Lao, Juan Shi, Jia Cao, Xiao Li, Xin Huang

“…The machine learning models were developed using five different algorithms, including logistic regression (LR), random forest (RF), gradient boosting machine (GBM), extreme gradient boosting model (XGBoost), and light gradient boosting machine (Light GBM).ResultsThe XGBoost model exhibited the most superior performance in predicting amikacin-associated AKI among the developed machine learning models. …”
Get full text

Partial-linear single-index Cox regression models with multiple time-dependent covariates by Myeonggyun Lee, Andrea B. Troxel, Sophia Kwon, George Crowley, Theresa Schwartz, Rachel Zeig-Owens, David J. Prezant, Anna Nolan, Mengling Liu

“…We developed an iterative estimation algorithm using spline techniques to model the nonparametric single-index component for potential nonlinear effects, followed by maximum partial likelihood estimation of the parameters. …”
Get full text

Results of the surgical treatment of diffuse pigmented villonodular synovitis (diffuse-type tenosynovial giant-cell tumor) of the knee by S. I. Herasymenko, O. A. Kostogryz, Yu. O. Kostogryz, A. M. Babko, V. M. Mayko

“…Using the method of mathematical statistics to evaluate the results obtained, we see that scores obtained through the Lysholm Scoring Scale were statistically significantly different in stages before a surgery (P = 0.000782), 3 months (P = 0.00005) and 6 months after the surgery (P = 0.04); but over time, these differences diminished and became actually insignificant 12 months after the surgery (P = 0.89). …”
Get full text

Combining machine learning with UAV derived multispectral aerial images for wheat yield prediction, in southern Brazil by Henrique dos Santos Felipetto, Erivelto Mercante, Octavio Viana, Adão Robson Elias, Giovani Benin, Lucas Scolari, Arthur Armadori, Diandra Ganascini Donato

“…This research aims to evaluate the performance of machine learning algorithms and multispectral aerial images in estimating wheat grain yield, contributing to the eradication of hunger and food security. …”
Get full text

An Adaptive Framework for Collective Anomaly Detection in Key Performance Indicators From Mobile Networks by Madalena Cilinio, Thaina Saraiva, Marco Sousa, Pedro Vieira, Antonio Rodrigues

“…Then, representative KPIs from each cluster are selected to evaluate the anomaly detection performance using two algorithms: the Smart Trouble Ticket Management (STTM) and STUMPY. …”
Get full text

Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy by Ben Cardoen, Hanene Ben Yedder, Ivan Robert Nabi, Ghassan Hamarneh

“…To evaluate these and future approaches, we introduce a mathematical framework, simplifying evaluation of existing and future algorithms. …”
Get full text

Enhancing acute leukemia classification through hybrid fuzzy C means and random forest methods by K. Lakshmi Narayanan, R. Santhana Krishnan, Y. Harold Robinson, S. Vimal, Tarik A. Rashid, Chetna Kausha, Md. Mehedi Hassan

“…In this proposed method the classification is tested with two Machine Learning algorithms which are Hybrid Fuzzy C Means (FCM) and Random Forest algorithm (RF) and Support Vector Machine for the detection and classification of Acute Leukemia disease and their performance was evaluated. …”
Get full text

FPGA-oriented lightweight multi-modal free-space detection network by Feiyi Fang, Junzhu Mao, Wei Yu, Jianfeng Lu

“…A real-time application of scene segmentation on KITTI-Road is used to evaluate our algorithm, and the model achieves a $ 94.39\% $ MaxF score and minimum 14 ms runtime on 20W FPGA devices.…”
Get full text