Machine learning - Strategic Insights Report (Page 38)

Machine learning

Advances in Chemicals and Chemistry: Improving Deposition Using Non-Dominant Sorting Genetic Algorithm-II

Researchers at the Department of Mechanical Engineering, Acad Technol, have made significant strides in improving the deposition of electroless nickel-copper-phosphorous coating using non-dominant sorting genetic algorithm-II. The team, led by Jhumpa De, aimed to develop predictive models using machine learning approaches to optimize the coating process. By varying the coating

Machine learning

Breakthrough Blood Test for Ovarian Cancer Detects Early Stages with High Accuracy

Ovarian cancer, a leading cause of gynecological cancer deaths worldwide, has been a challenging disease to diagnose due to its often-late detection. However, a recent development in the medical research community offers new hope. A simple blood test, trialled by UK and US researchers, has shown promising results in detecting

Machine learning

Breakthrough Blood Test for Ovarian Cancer Detection

Researchers have developed a simple blood test that can accurately detect ovarian cancer in its early stages, potentially improving care and outcomes for women with the disease. The test uses machine learning to recognize patterns in blood markers that are shed by cancer cells and has shown high accuracy in

Machine learning

New Machine Learning Framework for Cancer Diagnosis Offers High Accuracy and Interpretable Results

A team of researchers at Xi'an Jiaotong-Liverpool University has developed a novel machine learning framework, called OncoTrace-TOO, to accurately classify the tissue-of-origin in cancer patients, facilitating clinical diagnosis and personalized treatment. The framework utilizes gene expression profiles and identifies pan-cancer discriminative molecular features to achieve high predictive accuracy.

Machine learning

Machine Learning-Powered Smart Healthcare Systems Show Revolutionary Potential

The rapid increase in healthcare data has created a pressing need for customized and effective healthcare services. A new study has synthesised the convergence of artificial intelligence (AI) and big data through real-world case studies, cross-domain machine learning (ML) applications, and a critical discussion on ethical integration in smart diagnostics.

Machine learning

Federated Learning Framework for Multi-Domain Pattern Analysis

Research from Shenzhen University has made new findings in the area of Information Technology and Data Privacy. The study, focusing on Continual Learning (CL) and Federated Learning (FL), has introduced a novel framework that combines Graph Convolutional Networks (GCNs) and Vision Transformers (ViTs) with Family-based CL (FCL). This framework, named

Machine learning

Einocchio: A Breakthrough in Verifiable Cloud Computing

Researchers at Guizhou Normal University have made significant strides in addressing the challenges of data privacy and security in cloud computing. By proposing Einocchio, a verifiable computation scheme that combines Pinocchio system with homomorphic encryption, they have achieved IND-CPA security and demonstrated its effectiveness in cloud computing environments. This breakthrough

Machine learning

Novel Data-Driven Methodology for Calculating Insurance Premiums in Beijing

Researchers from North China University of Technology have proposed a novel data-driven methodology for calculating insurance premiums of Beijing-based insurance companies. This study utilized machine learning algorithms to predict healthcare insurance costs, incorporating 11 features such as age and weight as input variables. The research found that age was the

Machine learning

Machine Learning Advances Seafloor Sediment Classification with Physics-Inspired Models

Research conducted at Daejeon University in South Korea has utilized machine learning algorithms and oversampling techniques to classify seafloor sediments, achieving high accuracy rates. The study, funded by the National Research Foundation of Korea and the Ministry of Science & ICT, utilized field data including porosity, S- and P-wave velocities,

Machine learning

Machine Learning Model Developed to Evaluate Pilots' Mental Workload

A new study from the Civil Aviation University of China has introduced a data-driven psychophysiological model that uses machine learning algorithms to evaluate pilots' mental workload. The research, funded by the National Natural Science Foundation of China and Fundamental Research Funds for the Central Universities, involved a flight-simulation experiment

Machine learning

Machine Learning Models Exposed to Biases in Colorectal and Lung Cancer Research

Researchers from Rutgers University - The State University of New Jersey have conducted a study to explore the fairness of machine learning (ML) models in classifying colorectal and lung cancer patients. The study revealed that despite their potential to inform healthcare decisions, ML models are vulnerable to biases in data

Machine learning

Telepresence Robots Show Promise as Effective Alternative to Videoconferencing in Education

Researchers at George Mason University have discovered that telepresence robots can serve as a superior educational modality to videoconferencing, particularly in scenarios where in-person instruction is not feasible. The study, published in the International Journal of Social Robotics, found that participants who interacted with telepresence robots performed significantly better on

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