While multiple machine learning (ML) algorithms offered similar predictive performance, the cost-effective analysis revealed ...

Researchers at Rice University have developed a new machine learning (ML) algorithm ... parse light-based data for very subtle signals that are usually hard to pick up on using traditional methods ...

Their approach, based on continuous glucose monitoring (CGM) data, could improve early detection and risk ... 64 individuals without a prior diabetes diagnosis, using a CGM device, oral glucose ...

Benefits of Combining Circulating Tumor DNA With Tissue and Longitudinal Circulating Tumor DNA Genotyping in Advanced Solid Tumors: SCRUM-Japan MONSTAR-SCREEN-1 Study Osteosarcoma (OS) is the most ...

Orion Security employs a combination of proprietary AI models and fine-tuned open-source LLMs to automate data protection. “All our AI is something that we developed… we’re not using a third ...

This study validates a previously developed machine learning algorithm using real-world data. This algorithm may aid early diagnosis and can be used to quickly identify those who should have a ...

Now, researchers from Stanford Medicine have developed an artificial intelligence-based algorithm that uses data ... of type 2 diabetes via continuous glucose monitoring and machine learning ...

For example, it could collect data from targeted marketing campaigns, product inquiries, website engagement, customer feedback, and call center interactions. Using machine learning techniques ...

Using wavelength data to detect pulse waves, the research team used an AI algorithm to detect high blood pressure and diabetes from blood flow features ... of diabetes detection is improved ...

This paper presents a machine learning (ML)-based framework using ... data. 3. Our study compares the performance of the ANFIS model with traditional ML algorithms (SVM, Naïve Bayes, KNN) to ...

To address this issue, we propose a novel seismic phase detection algorithm ... data. This study modified an ML model that detects the phases of P- and S-waves of earthquake data for TL application.