Machine Learning– tag –
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RSC Publishing: Machine Learning-Augmented Lateral Flow Assays Dramatically Boost Sensitivity & Quantification in Infectious Disease POCT Diagnostics
Lab on a Chip (RSC Publishing) UK Overview Lateral Flow Assays (LFAs) are widely used as Point-of-Care (PoC) diagnostic platforms for infectious diseases due to their rapid operation, low cost, and user-friendly design. However, conventi... -
MARVEL Hub Catalyzes Over $800M in AI-Driven Materials Startup Funding, Bolstering Switzerland’s Innovation Ecosystem
Quantum Zeitgeist Switzerland Overview The NCCR MARVEL initiative has significantly contributed to AI-driven materials discovery, spawning four startups that collectively raised over $800 million in early-stage funding. MARVEL championed... -
AI & Machine Learning Weekly Report June 28, 2026
▼ ▼ ▼ If the infographic makes you want to read the full report, please click the download button below. ▼ ▼ ▼ 📄 Weekly Report June 28, 2026 (PDF) — Download Weekly Report June 28, 2026 (PDF) — DownloadDownload 🎙 Podcast June 28, 2026 (... -
arXiv Paper: Raman Data Fusion with Latent ODE Enhances Cell Culture Process Forecasting Accuracy
arXiv (Preprint) Global Overview New research published on arXiv proposes an innovative approach to improve cell culture process forecasting accuracy by fusing Raman spectroscopy data with a 'Multipath Adaptive Gated Bottleneck Latent OD... -
AI and Machine Learning Optimize Protein Design for Cost Efficiency in Large-Scale Production, Achieving 20-30% Energy Reduction
PatSnap Eureka Global Overview Optimizing protein design for maximizing cost efficiency in large-scale production is significantly advanced by computational algorithms, machine learning, molecular dynamics simulations, and artificial int... -
Cen-Online.org Details Breakthroughs and Industrial Applications in Catalyst Discovery Driven by Digital Tools and AI
Cen-Online.org Unknown Overview Cen-Online.org's article details recent advancements in catalysis and their industrial applications, highlighting how digital tools and AI are transforming catalyst discovery. Computational chemistry, mach... -
Institute of Science Tokyo Develops ML Framework to Infer Semiconductor Material Parameters with High Accuracy in Under 1 Millisecond from Transistor Measurements
Institute of Science Tokyo / Advanced Intelligent Systems Japan Overview Researchers at the Institute of Science Tokyo have developed a groundbreaking machine learning framework for solving inverse problems in semiconductor materials. Th... -
Frontiers Launches Research Topic on “High-Throughput AI-Driven Materials Discovery for High-Rate Batteries,” Accelerating Next-Gen Energy Storage
Frontiers Switzerland Overview Frontiers has initiated a new research topic, "High-Throughput AI-Driven Materials Discovery and Design for High-Rate Batteries," aiming to revolutionize battery material development through machine learnin... -
Digital Twin Technology Transforms Urban Development and Manufacturing, Demonstrated by Performance Monitoring and Prediction at NASA MAF
Axiom USA Overview Digital twin technology is revolutionizing diverse sectors from urban development to manufacturing, with dynamic digital replicas of physical assets linked to real-time data for performance monitoring, behavior predict... -
Machine Learning Predicts Thermal Properties of PHB/PHBV-Based Materials with Improved Accuracy Using Integrated Polymer Database
MDPI Switzerland Overview This study reports a novel machine learning (ML) approach for predicting thermal properties (glass transition temperature, melting point, crystallization temperature) of PHB and PHBV-based materials. By building...
