Streaming LiDAR Scene Flow Estimation by Mazen Abdelfattah, Z. Jane Wang, Rabab Ward

“…This work paves the way for deploying high-accuracy, real-time scene flow algorithms in autonomous driving, advancing the field towards more responsive and safer autonomous systems.…”
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The Philosophy of Semar as an Ethical Framework for the Use of Artificial Intelligence by Mohamad Khusnial Muhtar, Naufal Robbiqis Dwi

“…The Waspada principle highlights the&nbsp;</span><span style="font-size: 1rem;">importance of risk mitigation, addressing challenges such as algorithmic bias, privacy concerns, and&nbsp;</span><span style="font-size: 1rem;">unequal access to technology. 2) The integration of these ethical values presents an opportunity for&nbsp;</span><span style="font-size: 1rem;">strategic collaboration among developers, users, and policymakers to craft regulations that harmonize&nbsp;</span><span style="font-size: 1rem;">global standards with local wisdom, reinforcing the importance of culture-based ethics education. 3) Key&nbsp;</span><span style="font-size: 1rem;">challenges in implementation include limited cultural awareness in AI ethics discourse, resource&nbsp;</span><span style="font-size: 1rem;">constraints, and difficulties in aligning local ethical values with global regulatory frameworks. …”
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Research of color models in digital graphics by Hetman Oksana, Shpetna Svitlana

“…The prospects for further studies involve the development of advanced color processing algorithms and the integration of modern color models into emerging technologies such as augmented reality, virtual reality, and HDR imaging systems. …”
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A comparative study of Mongolian medicine prescriptions in the Chinese Pharmacopoeia and Tibetan medicinal compounds in the Ministerial Standards by Ji Zang, Cai Rang-Zhou Tai, Jie-Jia Nan, Cai Rang-Nanjia

“…Methods: A comparative analysis was conducted between Mongolian medicine prescriptions contained in the Chinese Pharmacopoeia and the corresponding Tibetan medicinal compounds included in the Ministerial Standards using Jaccard similarity coefficients and Hellinger distance algorithms across three dimensions: composition, shared drug dosage ratio, and efficacy. …”
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Prospective Validation and Usability Evaluation of a Mobile Diagnostic App for Obstructive Sleep Apnea by Pedro Amorim, Daniela Ferreira-Santos, Marta Drummond, Pedro Pereira Rodrigues

“…Current guidelines recommend the development of clinical prediction algorithms in screening prior to PSG. A recent intuitive and user-friendly tool (OSABayes), based on a Bayesian network model using six clinical variables, has been proposed to quantify the probability of OSA. …”
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Unmanned Aerial Surveillance and Tracking System in Forest Areas for Poachers and Wildlife by R. G. Sangeetha, Yash Srivastava, C. Hemanth, Harsh Sankar Naicker, Abhijith P. Kumar, Sreejith Vidhyadharan

“…The prototype designed to illustrate the proposed algorithms was powered by a 2200 mAh battery, allowing a flight duration of around 7 minutes.…”
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A Machine Learning Approach for Predicting Maternal Health Risks in Lower-Middle-Income Countries Using Sparse Data and Vital Signs by Avnish Malde, Vishnunarayan Girishan Prabhu, Dishant Banga, Michael Hsieh, Chaithanya Renduchintala, Ronald Pirrallo

“…Observations from our study demonstrate the feasibility of using sparse data and features for maternal health risk prediction using algorithms. By focusing on data from resource-constrained settings, we show that machine learning offers a convenient and accessible solution to improve prenatal care and reduce maternal deaths in LMICs.…”
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Elucidating the role of LGALS3BP in coronary atherosclerosis: integrating bioinformatics and machine learning for advanced insights by Suzhen Zhao, Chuanxin Zhao, Linlin Wang, Baoe Cheng, Man Zheng, Xiuyun Wang

“…The relationship between LGALS3BP expression and immune processes was explored using CIBERSORT and ESTIMATE algorithms, which indicated a positive association between higher LGALS3BP expression and increased immune cell infiltration. …”
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Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis by Ali Nabavi, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Farimah Safari

“…Multiple machine learning algorithms, including Random Forest, XGBoost, Gradient Boosting, Logistic Regression, CatBoost, and MLP, were optimized and evaluated. …”
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Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads by Mostafa M. Radwan, Sundus A. Faris, Ahmed Y. Barakat, Ahmad Mousa

“…Machine and deep learning algorithms have recently been more instrumental for forecasting pavement conditions. …”
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Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…The positive correlation between judge evaluations and sensor data indicates judges’ ability to evaluate overall gait quality. Three different algorithms were employed to predict the judges score from the IMU measurements: Support Vector Machine (SVM), Gradient Boosting Machine (GBM), and K-Nearest Neighbors (KNN). …”
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Outpatient diagnosis of endogenous intoxication in surgery by A. A. Solomakha, A. P. Vlasov, V. I. Gorbachenko

“…Statistical, neural network and algorithms with elements of fuzzy neural networks were used on a sample consisting of hematological parameters of 274 patients with chronic kidney disease and healthy ones based on 25 laboratory parameters. …”
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Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis. by Claudia Bühnemann, Simon Li, Haiyue Yu, Harriet Branford White, Karl L Schäfer, Antonio Llombart-Bosch, Isidro Machado, Piero Picci, Pancras C W Hogendoorn, Nicholas A Athanasou, J Alison Noble, A Bassim Hassan

“…Using material from cohorts of genetically diagnosed Ewing sarcoma with EWSR1 chromosomal translocations, confocal images of tissue microarrays were segmented with level sets and watershed algorithms. Each cell nucleus and cytoplasm were identified in relation to DAPI and CD99, respectively, and protein biomarkers (e.g. …”
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Species delimitation and microalgal cryptic diversity analysis of the genus Micractinium (Chlorophyta) by E. S. Krivina, A. D. Temraleeva, Yu. S. Bukin

“…Phylogenetic analysis showed that the genus Micractinium is characterized by high cryptic diversity. The algorithms used for species delimitation had different results on the number of potentially species-level clusters allocated. …”
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Research on the correlation between retinal vascular parameters and axial length in children using an AI-based fundus image analysis system. by Chaoyang Zhao, Huilin Li, Ziyou Yuan, Zihan Yang, Tiantian Wang, Yan Wang, Qian Tong, Shaofeng Hao

“…Subsequently, these fundus images were meticulously analyzed using the EVision AI fundus image analysis system, which is a commercial software that employs pre-trained algorithms to automatically extract retinal vascular parameters.Pearson and Spearman correlation coefficients were used to analyze the correlation between retinal vascular parameters and axial length, and multiple linear regression analysis was further conducted to explore their intrinsic associations.…”
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Hybrid AI and semiconductor approaches for power quality improvement by Ravikumar Chinthaginjala, Asadi Srinivasulu, Anupam Agrawal, Tae Hoon Kim, Sivarama Prasad Tera, Shafiq Ahmad

“…The research addresses key power quality challenges - including voltage sags, swells, harmonics, and transient disturbances - through a data-driven framework that combines traditional control techniques with adaptive learning models. A variety of algorithms, including Support Vector Machines (SVM), Random Forests, Neural Networks, Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks, were tested using real-time data. …”
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Machine learning−derived multivariable predictors of postcardiotomy cardiogenic shock in high-risk cardiac surgery patientsCentral MessagePerspective by Edward G. Soltesz, MD, MPH, Randi J. Parks, PhD, Elise M. Jortberg, MS, Eugene H. Blackstone, MD

“…In total, 68 preoperative clinical variables were considered in machine-learning algorithms trained and optimized using scikit-learn software. …”
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Evaluation of Diagnostic Recommendations Embedded in Medication Alerts: Prospective Single-Arm Interventional Study by Yu-Chen Liu, Guan-Ling Lin, Jeremiah Scholl, Yi-Chun Hung, Yu-Jing Lin, Yu-Chuan Li, Hsuan-Chia Yang

“…The system provided diagnostic recommendations based on machine learning algorithms trained on data from the National Health Insurance Research Database. …”
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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…By leveraging advanced algorithms and machine learning techniques, the research aims to streamline the allocation of tasks and responsibilities among various stakeholders, including farmers, agronomists, technicians, and AI systems. …”
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Nondestructive discrimination of advanced clones and cultivars of strawberry using an innovative approach involving image analysis and machine learning by Ewa Ropelewska, Agnieszka Masny

“…As many as 2172 image parameters were extracted from the image of each fruit converted to different color channels R, G, B, L, a, b, X, Y, Z, U, V, and S and textures with the highest discriminative power were selected to develop models using various machine learning algorithms, such as Multilayer Perceptron, MultiClass Classifier, IBk, and LMT, Linear Discriminant, Quadratic SVM, Subspace Discriminant, and Wide Neural Network. …”
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