Machine learning
A new study has introduced a novel machine learning-based strategy for generating supercapacitor reference current to optimize energy distribution in Battery Electric Vehicles (BEV) and Hybrid Battery Electric Vehicles (HBEV). Researchers from the School of Electrical Engineering have developed a Long Short-Term Memory (LSTM) neural network trained using real-world drive
Machine learning
Research conducted by the School of Computer Science and Information Technology has shed light on the effectiveness of machine learning algorithms in predicting relationship dynamics during initial meetings. The study analyzed various models, including Light Gradient Boosting Classification (LGBC), in conjunction with the Henry Gass Solubility Optimization Algorithm (HGSOA), Flying
Machine learning
Researchers at Fudan University in Shanghai, China have proposed a machine learning-enhanced model-based optical proximity correction (MBOPC) framework that employs a convolutional neural network (CNN) to predict mask edge imaging thresholds. This innovation addresses accuracy bottlenecks in traditional MBOPC techniques due to physical modeling errors. The CNN-based variable threshold strategy
Machine learning
Researchers from Kharkiv National University of Radio Electronics have conducted a study on the tokenization efficiency of foundational large language models (LLMs) for the Ukrainian language. The study, published in Frontiers in Artificial Intelligence, aimed to investigate the current state-of-the-art models' performance in general-purpose language and specific domains, as
Machine learning
Researchers have made a groundbreaking discovery in the development of a blood test that can accurately detect ovarian cancer at its earliest stages, potentially transforming the way the disease is diagnosed and treated. The innovative test, created by AOA Dx, uses machine learning to identify two distinct blood markers in
Machine learning
STMicroelectronics International N.V., a leading semiconductor manufacturer, has filed a patent application for a novel in-sensor fall detection system. According to the application, the system is designed to detect falls using a pressure sensor and an inertial measurement unit (IMU), eliminating the need for machine learning techniques that consume
Machine learning
Modern network infrastructures have significantly improved global connectivity but have also escalated network security challenges as sophisticated cyberattacks increasingly target vital systems. Intrusion Detection Systems (IDSs) play a crucial role in identifying and mitigating these threats. Recent advances in machine-learning-based IDSs have shown promise in detecting evolving attack patterns. Researchers
Machine learning
Investigations into sensor research have led to a significant breakthrough in the field of vehicular edge computing. According to a new study, efficient task offloading for delay-sensitive applications like autonomous driving poses substantial challenges in multi-hop Vehicular Edge Computing (VEC) networks due to high vehicle mobility, dynamic network topologies, and
Machine learning
A new study from the Department of General Surgery at Mianyang Hospital of Traditional Chinese Medicine, People's Republic of China, has developed and validated a machine learning-based nomogram for preoperative prediction of laparoscopic surgical difficulty in gallstone patients. The research aimed to improve surgical outcomes by incorporating key
Machine learning
Researchers at the MUSC Hollings Cancer Center have developed a high-accuracy AI model using natural language processing (NLP) to extract critical details from medical records. The model can help doctors determine important information for patient treatment, particularly in cases of metastatic tumors affecting the brain. By automating data extraction from
Machine learning
ChemImage Corporation has patented a new medical imaging system designed to improve intraoperative imaging for surgeons. The patent, filed on September 21, 2020, and published on July 29, 2025, describes a system that uses multiple illuminating photons to generate real-time images displayed in stereo vision, enabling surgeons to differentiate anatomical
Machine learning
A new report highlights the profound impact of artificial intelligence (AI) on medicine, with radiology being a pioneer in this transformation. As digitalization and advances in computer technology accelerate, AI is redefining cognitive work in healthcare, automating workflows, enhancing image acquisition and interpretation, and improving diagnostic precision. Despite concerns regarding
