Enhanced Fall Detection Using YOLOv7-W6-Pose for Real-Time Elderly Monitoring by Eugenia Tîrziu, Ana-Mihaela Vasilevschi, Adriana Alexandru, Eleonora Tudora

“…This study aims to enhance elderly fall detection systems by using the YOLO (You Only Look Once) object detection algorithm with pose estimation, improving both accuracy and efficiency. …”
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A CART-Based Model for Analyzing the Shear Behaviors of Frozen–Thawed Silty Clay and Structure Interface by Fengpan Zhu, Bo Wang, Zhiqiang Liu

“…This study employs integrated machine learning algorithms to model the shear behavior of frozen–thawed silty clay and the structure interface. …”
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Application of Machine Learning and Multi-Dimensional Perception in Urban Spatial Quality Evaluation: A Case Study of Shanghai Underground Pedestrian Street by Tianning Yao, Yao Xu, Liang Sun, Pan Liao, Jin Wang

“…It then gathers multidimensional perception data from selected locations and ultimately analyses and predicts the results employing machine learning techniques, specifically Random Forest and XGBoost. …”
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Older people and the smart city – Developing inclusive practices to protect and serve a vulnerable population by Aaro Tupasela, Juanita Devis Clavijo, Marjut Salokannel, Christoph Fink

“…In this article, we report on the main challenges encountered during the implementation of the URBANAGE project, and the development of the components for big data analytics, visualisations, predictive algorithms and simulation. Using examples from three European locations – Helsinki, Flanders and Santander – we describe and discuss how we can gather personal data related to the daily lives of older people in terms of the existing privacy and data protection laws in the EU. …”
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A Numerical Laboratory for Simulation of Flanged Reinforced Concrete Shear Walls by Alireza Khaloo, Mohammad Tabiee, Hatef Abdoos

“…In order to validate FlashLab, this paper numerically simulates T-, H-, and L-shaped RC shear walls and compares the results to the experimental data, indicating good agreement between the numerical and experimental results to an extent that the proposed numerical laboratory is capable of predicting the backbone curve with an accuracy more than 90 percent. …”
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An IoT-Driven Real-Time Skin Disease Detection System using Machine Learning by Aliya Aftab, Dr.Hina Sattar, Muhammad Farhan Aslam, Touseef Hussain, Syeda Sitara Waseem

“…IoT will measure body temperature, and a deep learning algorithm and CNN algorithm predict the diseases. The output is provided on the GUI as an Android application, in order to help them understand whether they have skin diseases and allergies early. …”
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Neural Networks in Forecasting Disease Dynamics by A. G. Hasanov, D. G. Shaybakov, S. V. Zhernakov, A. M. Men’shikov, F. F. Badretdinova, I. F. Sufiyarov, J. R. Sagadatova

“…The best convergence of the network learning process is provided by the quasi-Newton and conjugated gradient algorithms. In order to assess the effectiveness of the proposed neural network in predicting the dynamics of inflammation, a comparative analysis was carried out using a number of conventional methods, such as exponential smoothing, moving average, least squares and group data handling.Conclusion.The proposed neural network based on approximation and extrapolation of variations in the patient’s medi‑ cal history over fixed time window segments (within the ‘sliding time window’) can be successfully used for forecasting the development and outcome of erysipelas.…”
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Healthcare Economics-Vital Threat Detection System Efficiency: A Business Process Analysis Methodology by Salma Elhag, Amal Alghamdi, Amal Alahmari, Abeer Alharbi

“…The data is sent to the cloud, where it is stored and analyzed using artificial intelligence (AI) algorithms to predict critical health conditions. When any abnormalities are detected, immediate alerts are sent to family members or caregivers via mobile applications, enabling a quick response. …”
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Estimating Aggregate Capacity of Connected DERs and Forecasting Feeder Power Flow With Limited Data Availability by Amir Reza Nikzad, Amr Adel Mohamed, Bala Venkatesh, John Penaranda

“…The method is tested using a North American utility feeder data, achieving an average accuracy of 95.56% for forecasting aggregate load power, 93.70% for feeder flow predictions, and 97.53% for estimating the aggregate capacity of DERs.…”
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Analysis of State-of-Charge Estimation Methods for Li-Ion Batteries Considering Wide Temperature Range by Yu Miao, Yang Gao, Xinyue Liu, Yuan Liang, Lin Liu

“…Accurate state-of-charge (SOC) estimation is critical for optimizing battery performance, ensuring safety, and predicting battery lifetime. However, SOC estimation faces significant challenges under extreme temperatures and complex operating conditions. …”
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Toward Street‐Level Nowcasting of Flash Floods Impacts Based on HPC Hydrodynamic Modeling at the Watershed Scale and High‐Resolution Weather Radar Data by Pierfranco Costabile, Carmelina Costanzo, John Kalogiros, Vasilis Bellos

“…Abstract In our era, the rapid increase of parallel programming coupled with high‐performance computing (HPC) facilities allows for the use of two‐dimensional shallow water equation (2D‐SWE) algorithms for simulating floods at the “hydrological” catchment scale, rather than just at the “hydraulic” fluvial scale. …”
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A survey on exploring the challenges and applications of wireless body area networks (WBANs) by Arun Sekar Rajasekaran, L. Sowmiya, Azees Maria, R. Kannadasan

“…Due to the arrival of the Micro Electromechanical System (MEMS) and several intelligent sensors, collaboration with WBAN makes accurate predictions of parameters in the human body. WBAN has numerous applications in medical and non-medical fields. …”
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The role of hematological parameters as predictors of mortality in elderly patients in the hospital period by L. V. Borisova, S. A. Rukavishnikova, A. S. Pushkin, T. A. Ahmedov, V. V. Yakovlev

“…The development of algorithms for predicting adverse outcomes, including death in elderly and senile patients, is an urgent issue. …”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…Global models, such as flux balance analysis (FBA), integrate genome-scale networks to predict cellular behavior and optimize production conditions. …”
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FEATURES OF THE TREATMENT OF HYPERMOBILITY OF THE ARTICULAR HEADS AND DISLOCATIONS OF THE LOWER JAW ON THE BACKGROUND OF FRACTURES OF THE CONDYGAL PROCESSES OF THE MANDIBLE, AS A P... by O.A. Toropov, D.S. Avetikov, M.G. Skikevych, O.S. Ivanytska, O.O. Rozkolupa, K.P. Lokes

“…The analysis of clinical case data allows us to state that the goal of treatment should be to return the condyles to their original physiological position, and conservative methods should be in the first place when creating an algorithm. Early manual reduction of the joint heads is the best method of treatment, if it is possible to carry it out in a timely manner. …”
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Determination of Colles fracture risk index by X-ray images with the computer vision application by Wisam A. Hussein, Hussain J. AlKhatteib, Jawad K. Abbas

“…Background. Modelling a predictive risk index for Colles fractures using X-ray image analysis is a crucial application in orthopaedics since these fractures have essential health and economic burdens, particularly among the elderly. …”
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Survival analysis using machine learning in transplantation: a practical introduction by Andrea Garcia-Lopez, Maritza Jiménez-Gómez, Andrea Gomez-Montero, Juan Camilo Gonzalez-Sierra, Santiago Cabas, Fernando Giron-Luque

“…The integration of machine learning techniques, particularly the Random Survival Forest (RSF) model, offers potential enhancements to predictive modeling and decision-making. This study aims to provide an introduction to the application of the RSF model in survival analysis in kidney transplantation alongside a practical guide to develop and evaluate predictive algorithms. …”
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Machine learning analysis of molecular dynamics properties influencing drug solubility by Zeinab Sodaei, Saeid Ekrami, Seyed Majid Hashemianzadeh

“…The Gradient Boosting algorithm achieved the best performance with a predictive R2 of 0.87 and an RMSE of 0.537 in test set. …”
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Diagnostic value of leukocytosis in patients presenting to the emergency department with abdominal pain: A retrospective observational study by Erkan Boğa

“…Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of leukocytosis in predicting surgical needs were calculated. …”
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SCoralDet: Efficient real-time underwater soft coral detection with YOLO by Zhaoxuan Lu, Lyuchao Liao, Xingang Xie, Hui Yuan

“…By incorporating soft labels and soft central region loss, our model is guided to prioritize high-quality, well-aligned predictions. We evaluate SCoralDet on the Soft-Coral dataset, achieving an inference latency of 9.52 ms and an mAP50 of 81.9. …”
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