Diagnosis and treatment of ovarian cancer in the light of modern molecular genetic achievements by E. M. Kagirova, R. I. Khusainova, I. R. Minniakhmetov

“…Ovarian cancer is the leading cause of death in women diagnosed with gynecological cancer. ovarian cancer is a heterogeneous disease composed of different types of tumors, each of which has differences in pathogenesis, spectrum and mutation frequencies in characteristic genes, response to therapy and prognosis of the disease. more than 80 % of all malignant ovarian tumors are of epithelial origin (carcinomas) and about 26 % of all cases of ovarian cancer are caused by germline mutations found in the BRCA1/BRCA2 genes. to date, the priority areas in the study of ovarian cancer are the improvement of diagnostic methods, algorithm of examination of women, identification of new biomarkers, study of tumor microenvironment and composition of ascitic fluid to detect cancer at early stages and prescribe appropriate therapy. …”
Get full text

Exploration of the shared pathways and common biomarkers in cervical and ovarian cancer using integrated bioinformatics analysis by Fang Liu, Min Wang, Tian Zhu, Cong Xu, Guangming Wang

“…Finally, the CIBERSORT algorithm was used to estimate the immune infiltration levels of CC and OC, and the correlation between immune cell infiltration and common biomarkers was explored. …”
Get full text

Results of trawl counts for juvenile pink salmon in the Bering and Okhotsk Seas in 2024 and prospects for the returns and catch in the Karaginsky subzone and Okhotsk Sea in 2025 by A. A. Somov, E. A. Shevlyakov, A. N. Starovoitov, V. A. Shevlyakov, I. V. Melnikov

“…The key stage of juvenile pink salmon monitoring is the survey of their fall feeding in the sea that detects the year-class strength. The results of this survey are used for forecasting of the pink salmon returns to the Karaginsky fishing subzone in Bering Sea and to the Okhotsk Sea and the landing in the next year. …”
Get full text

All-day free-space quantum key distribution with thermal source towards quantum secure communications for unmanned vehicles by Hanwen Yin, Peng Huang, Zehao Zhou, Tao Wang, Xueqin Jiang, Guihua Zeng

“…Specifically, a novel scheme is proposed to reduce excess noise from PSP, and efficient quantum coherence detection alongside advanced digital signal processing algorithms is developed to achieve low-noise synchronized raw data acquisition. …”
Get full text

Research Progress on Vehicle Status Information Perception Based on Distributed Acoustic Sensing by Wenqiang Dong, Xin Cheng, Jingmei Zhou, Wei Liu, Jianjin Gao, Chuan Hu, Xiangmo Zhao

“…This study first reviews the limitations of conventional vehicle detection technologies and introduces the operating principles and technical features of DAS. …”
Get full text

Automated analysis and textual summarization of time-varying references in advanced greenhouse climate control by Ramesh Arvind Naagarajan, Kiran Kumar Sathyanarayanan, Nadja Bauer, Stefan Streif, Stefan Streif

“…Potential reasons are the lack of transparency and the understandability of the control algorithms. This study introduces a language-based support system to improve the usability of advanced control strategies like MPC. …”
Get full text

Machine Learning Applied to Improve Prevention of, Response to, and Understanding of Violence Against Women by Mariana Carolyn Cruz-Mendoza, Roberto Angel Melendez-Armenta, Juana Canul-Reich, Julio Muñoz-Benítez

“…The methodology integrates Random Forest (RF) and Gradient Boosting Classifier (GBC) algorithms to classify IPV cases by leveraging historical data for predictive analysis. …”
Get full text

Method for Preprocessing Video Data for Training Deep-Learning Models for Identifying Behavioral Events in Bio-Objects by Marina Barulina, Alexander Andreev, Ilya Kovalenko, Ilya Barmin, Eduard Titov, Danil Kirillov

“…The advent of deep-learning algorithms has made it possible to automate the qualitative and quantitative analysis of the behavior of bio-objects recorded in video format. …”
Get full text

Proactive Complaint Management in Public Sector Informatics Using AI: A Semantic Pattern Recognition Framework by Marco Esperança, Diogo Freitas, Pedro V. Paixão, Tomás A. Marcos, Rafael A. Martins, João C. Ferreira

“…Conventional keyword-based approaches are inadequate for detecting semantically similar issues expressed in diverse ways. …”
Get full text

Artificially intelligent nasal perception for rapid sepsis diagnostics by Joonchul Shin, Gwang Su Kim, Seongmin Ha, Taehee Yoon, Junwoo Lee, Taehoon Lee, Woong Heo, Kyungyeon Lee, Seong Jun Park, Sunyoung Park, Jaewoo Song, Sunghoon Hur, Hyun-Cheol Song, Ji-Soo Jang, Jin-Sang Kim, Hyo-Il Jung, Chong-Yun Kang

“…In this study, we designed colorimetric gas sensor arrays, which change color upon interaction with biomarkers, offer a direct visual signal, and demonstrate high sensitivity and specificity in detecting sepsis-related VOCs. Furthermore, an artificial intelligence (AI) based algorithm, Rapid Sepsis Boosting (RSBoost), was employed as an analytical technique to enhance diagnostic accuracy (96.2%) in blood sample. …”
Get full text

Neuromorphic principles for machine olfaction by Nik Dennler, Aaron True, André van Schaik, Michael Schmuker

“…Further, we critically review and discuss the literature on neuromorphic olfaction; particularly focusing on neuromorphic principles such as event generation algorithms, information encoding mechanisms, event processing schemes (spiking neural networks), and learning. …”
Get full text

Machine Learning Techniques in Chronic Kidney Diseases: A Comparative Study of Classification Model Performance by Nguyen Dong Phuong, Nguyen Trung Tuyen, Vu Thi Thai Linh, Nghi N Nguyen, Thanh Q Nguyen

“…Machine learning models can assist physicians in this task by providing fast and accurate detection. As a result, many health care systems have adopted machine learning, especially for disease diagnosis. …”
Get full text

Applications of quantum computing in clinical care by Stevan C. Fairburn, Stevan C. Fairburn, Lara Jehi, Brenton T. Bicknell, Beckley G. Wilkes, Bharat Panuganti

“…The studies were evaluated for their contributions to diagnostic, therapeutic, and decision-support improvements in clinical care enabled by quantum computing technologies.ResultsThe analysis revealed QC’s promise in improving diagnostic accuracy in medical imaging, optimizing treatments in oncology, and enhancing real-time clinical decision-making. QC-driven algorithms demonstrated potential to enhance diagnostic accuracy and computational efficiency. …”
Get full text

Potential use of saliva infrared spectra and machine learning for a minimally invasive screening test for congenital syphilis in infants by Deise Cristina Dal’Ongaro, Cicero Cena, Bruno Spolon Marangoni, Daniele A. Soares-Marangoni

“…This study aimed to explore the development of a method for the diagnosis of congenital syphilis using saliva FTIR spectra and machine learning algorithms in infants aged 0 to 12 months. First, the potential of FTIR for analyzing infant saliva was evaluated. …”
Get full text

Unmanned Ground Vehicles for Continuous Crop Monitoring in Agriculture: Assessing the Readiness of Current ICT Technology by Maurizio Agelli, Nicola Corona, Fabio Maggio, Paolo Vincenzo Moi

“…Key aspects considered include algorithms for in-field navigation, AIoT models for detecting agricultural emergencies, and advanced edge devices that are capable of managing sensors, collecting data, performing real-time deep learning inference, ensuring precise mapping and navigation, and sending alert reports with minimal human intervention. …”
Get full text

Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

“…The machine learning algorithms such as SVM and Logistic Regression have been used to classify the nodules based on the features. …”
Get full text

Analysis of the capabilities of an information system for improving sleep quality based on biometric data analysis by M.S. Graf, A.V. Yakoniuk, D.V. Krant, I.I. Golovach

“…The system is able to function independently thanks to the use of machine learning algorithms, including LSTM for prediction, Kalman filter for data cleaning, Isolation Forest for anomaly detection, and K-means for clustering sleep patterns.…”
Get full text

The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns by Lianne Grin, Sieglinde Bogaert, Saskia Wijnands, Arnold Besselaar, Marieke van der Steen, Jesse Davis, Benedicte Vanwanseele

“…Machine learning algorithms have the capacity to analyse such complex nonlinear relationships, offering the potential to train a model that assesses whether a child has relapsed clubfoot based on their movement pattern. …”
Get full text

Insights and caveats from mining local and global temporal motifs in cryptocurrency transaction networks by Naomi A. Arnold, Peijie Zhong, Cheick Tidiane Ba, Ben Steer, Raul Mondragon, Felix Cuadrado, Renaud Lambiotte, Richard G. Clegg

“…Studying motif completion time reveals dynamics driven by human behaviour as well as algorithmic behaviour.…”
Get full text

Seismic Data Acquisition Utilizing a Group of UAVs by Artem Timoshenko, Grigoriy Yashin, Valerii Serpiva, Rustam Hamadov, Dmitry Fedotov, Mariia Kartashova, Pavel Golikov

“…The architecture of the swarm control station, its individual blocks, features of UAV exploitation for seismic data acquisition tasks, hardware and software tool limitations are considered. Algorithms for planning UAV swarm flight paths, their comparison and trajectory examples are presented. …”
Get full text