Modelos univariados de séries temporais para previsão das temperaturas médias mensais de Erechim, RS Univariate time series methods for forecasting the monthly mean air temperature... by Leonardo Chechi, Fábio M. Bayer

“…In the class of ARIMA models using criteria information, SARIMA type models that consider the seasonal characteristics of air temperature were selected, whereas for exponential smoothing models Holt-Winters additive algorithm were used. Smoothing constants are determined to minimize the mean square error between observed and predicted values. …”
Get full text

Detecting Freezing of Gait in Parkinson Disease Using Multiple Wearable Sensors Sets During Various Walking Tasks Relative to Medication Conditions (DetectFoG): Protocol for a Pros... by Sébastien Cordillet, Sophie Drapier, Frédérique Leh, Audeline Dumont, Florian Bidet, Isabelle Bonan, Karim Jamal

“…There is no consensus on the number and location of IMU, type of algorithm, and method of triggering and scoring the FoG episodes. …”
Get full text

G4 & the balanced metric family – a novel approach to solving binary classification problems in medical device validation & verification studies by Andrew Marra

“…A new metric called G4 is presented, which is the geometric mean of sensitivity, specificity, the positive predictive value, and the negative predictive value. …”
Get full text

Primary Care Physician Use of Elastic Scattering Spectroscopy on Skin Lesions Suggestive of Skin Cancer by Stephen P. Merry, Ivana T. Croghan, Kimberly A. Dukes, Brian C. McCormick, Gerard T. Considine, Michelle J. Duvall, Curtis T. Thompson, David J. Leffell

“…Objectives: To evaluate the performance of noninvasive, elastic scattering spectroscopy, algorithm-powered device (DermaSensor) to detect melanoma and basal and squamous cell cancers in the primary care setting. …”
Get full text

Effect of Molarity of Sodium Hydroxide on the Strength Behavior of Fiber-Reinforced Geopolymer Concrete Exposed to Elevated Temperature by Abbasali Saffar, Mohammad Ehsanifar, Seyed Mohammad Mirhoseini, Mohammad Javad Taheri Amiri

“…Beside, post-fire strength of FRGPC was predicted using artificial neural network (ANN) and support vector machines (SVM) with the integration of water cycle algorithm (WCA). …”
Get full text

Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…The results indicate that Ensemble Learning and AdaBoost yield the highest accuracy algorithms in prediction capability as they tend to illustrate the lowest values of mean squared error and mean absolute relative error (%) and highest R-squared values. …”
Get full text

“VisualFields Easy”: an iPad Application as a Simple Tool for Detecting Visual Field Defects by Angelane S. Santos, MD, Evelyn S. Morabe, MD

“…Purpose/Objective: This study aims to determine the reliability of the “VisualFields Easy” application in detecting visual field loss among ophthalmology patients; and to determine the sensitivity, specificity, positive predictive and negative predictive values of this examination using the Humphrey Visual Field Analyzer as the gold standard. …”
Get full text

Development of clinical decision support for patients older than 65 years with fall-related TBI using artificial intelligence modeling. by Biche Osong, Eric Sribnick, Jonathan Groner, Rachel Stanley, Lauren Schulz, Bo Lu, Lawrence Cook, Henry Xiang

“…Data were split into two sets, where 80% developed a decision tree, and 20% tested predictive performance. We employed a conditional inference tree algorithm with bootstrap (B = 100) and grid search options to grow the decision tree and measure discrimination ability using the area under the curve (AUC) and calibration plots.…”
Get full text

Developing and validating a drug recommendation system based on tumor microenvironment and drug fingerprint by Yan Wang, Xiaoye Jin, Rui Qiu, Bo Ma, Sheng Zhang, Xuyang Song, Jinxi He

“…This study aimed to develop a personalized drug recommendation model leveraging genomic profiles to optimize therapeutic outcomes.MethodsA content-based filtering algorithm was implemented to predict drug sensitivity. …”
Get full text

Hybrid Series of Carbon‐Vacancy Electrodes for Multi Chemical Vapors Diagnosis Using a Residual Multi‐Task Model by Tianci Liu, Yun Ji Hwang, Lu Zhang, Jongwoo Hong, Teajong Hwang, Seong Chan Jun

“…Artificial intelligence (AI) integrated gas sensor systems effectively enable multi‐gas detection using specialized algorithms. Nevertheless, these algorithms are prone to overfitting owing to their high model complexity; this study proposes a sensor array that engineers carbon vacancies in graphene oxide via metal ion doping and high‐temperature reduction, enabling high‐sensitivity, simultaneous detection of various gases at low temperatures (20 °C). …”
Get full text

Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
Get full text

The PLSR-ML fusion strategy for high-accuracy leaf potassium inversion in karst region of Southwest China by Zhihao Song, Zhihao Song, Wen He, Yuefeng Yao, Ling Yu, Jinjun Huang, Yong Xu, Haoyu Wang

“…Validation coefficient of determination (R²) values reached 0.89, 0.94, and 0.96, respectively—representing improvements of 206%, 147%, and 108% over standalone algorithms. This performance gain was attributed to rigorous overfitting control: PLSR’s dimensionality reduction synergized with ensemble machine learning (RF, XGBoost, MLP) to eliminate redundant spectral features while retaining predictive signals. …”
Get full text

Machine learning applications in the analysis of sedentary behavior and associated health risks by Ayat S Hammad, Ayat S Hammad, Ali Tajammul, Ismail Dergaa, Ismail Dergaa, Ismail Dergaa, Maha Al-Asmakh, Maha Al-Asmakh

“…The review highlights the utility of various ML approaches in classifying activity levels and significantly improving the prediction of sedentary behavior, offering a promising approach to address this widespread health issue.ConclusionML algorithms, including supervised and unsupervised models, show great potential in accurately detecting and predicting sedentary behavior. …”
Get full text

Machine learning and thermodynamic modeling for optimizing hydrogen production via algae-biomass co-gasification by Thanadol Tuntiwongwat, Takashi Yukawa, Thongchai Rohitatisha Srinophakun, Kanit Manatura, Somboon Sukpancharoen, Seyedali Mirjalili

“…Three microalgae species (Chlorella vulgaris, Nannochloropsis oculata, Fucus serratus) were co-gasified with biomass feedstocks (Fir Pellet (FP), Palm Empty Fruit Bunch (PEFB), Pellet Pine Wood (PPW)) using Aspen Plus® simulation based on Gibbs free energy minimization. Six ML algorithms (XGB, RF, SVR, KNN, ANN, DT) with Shapley additive explanations (SHAP) analysis predicted H2 yield and syngas lower heating value (LHV) from 3609 data points across 24 input parameters. …”
Get full text

Exploring the possibilities of MADDPG for UAV swarm control by simulating in Pac-Man environment by Artem Novikov, Sergiy Yakovlev, Ivan Gushchin

“…Traditional Rule-Based Pursuit and Prediction Algorithms inspired by the behaviors of Blinky and Pinky ghosts from the classic Pac-Man game are included as benchmarks to assess the impact of learning-based methods. …”
Get full text

Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models by Nedhal Al-Husaini, Rozaimi Razali, Amal Al-Haidose, Mohammed Al-Hamdani, Atiyeh M. Abdallah

“…Here we applied machine learning (ML) algorithms to predict low femoral neck BMD using standard demographic and laboratory parameters. …”
Get full text

Identifying potential three key targets gene for septic shock in children using bioinformatics and machine learning methods by Wei Guo, Hao Chen, Feng Wang, Yingjiao Chi, Wei Zhang, Shan Wang, Kezhu Chen, Hong Chen

“…Three machine learning algorithms LASSO, random forest (RF), and support vector machine recursive feature elimination (SVM-RFE) were used to finally screen out three core genes: CD163, MCEMP1 and RETN. …”
Get full text

Modeling Worldwide Tree Biodiversity Using Canopy Structure Metrics from Global Ecosystem Dynamics Investigation Data by Jin Xu, Kjirsten Coleman, Volker C. Radeloff, Melissa Songer, Qiongyu Huang

“…Using Forest Global Earth Observatory (ForestGEO) data, we developed three models using the random forest algorithm to predict global tree species richness across climate zones, including a dynamic habitat index (DHI)-only model, a GEDI-only model, and a combined GEDI-DHI model. …”
Get full text

Artificial intelligence for severity triage based on conversations in an emergency department in Korea by Jae Won Seo, Sung-Joon Park, Young Jae Kim, Jung-Youn Kim, Kwang Gi Kim, Young-Hoon Yoon

“…To achieve this, artificial intelligence algorithms that consider the frequency and order of words used in the conversation were employed alongside neural network models. …”
Get full text

Vehicle-to-everything decision optimization and cloud control based on deep reinforcement learning by Zhenhai Gao, Dayu Liu, Chengyuan Zheng

“…In the decision-making module, deep reinforcement learning algorithms are applied to optimize decision processes by maximizing expected rewards. …”
Get full text