QLattice® publications, preprints, and Gartner® reports.
Browse publications and reports that cite Abzu's QLattice® artificial intelligence (AI) algorithm.
Researchers and and scientists cite Abzu’s QLattice in publications for introducing a new standard of performance and explainability to data sets. Learn more about Abzu’s proprietary technology and see the Gartner® reports that mention the QLattice.
Predicting weight loss success on a new Nordic diet: an untargeted multi-platform metabolomics and machine learning approach.
A novel QLattice-based whitening machine learning model of landslide susceptibility mapping.
Plasma proteomics discovery of mental health risk biomarkers in adolescents.
Analysis of the relationship between fetal health prediction features with machine learning Feyn QLattice regression model.
What is the QLattice?
The QLattice artificial intelligence (AI) algorithm is a supervised machine learning method for symbolic regression.
Models developed by the QLattice have unparalleled accuracy, even with very little data, and are uniquely simple to understand.
Invented by Casper Wilstrup and developed in-house by Abzu, the technology behind the QLattice is patented. Read the press release about our patent for more information.
Are you a scientist or a researcher?
Good news if you want to cite Abzu's QLattice as part of your research.
Abzu’s QLattice is free for noncommercial use.
Gartner® mentions the QLattice as explainable and trustworthy AI.
From market guides to industry trends to Cool Vendor™, Abzu’s QLattice has been mentioned in Gartner® research.
See Garther® research guides, trends, and more that cite Abzu’s QLattice. To access Gartner research, you must have a client account.
Market Guide for AI Trust, Risk, and Security Management.
Initiatives: Artificial Intelligence
AI brings new trust, risk and security management challenges that conventional controls do not address. Data and analytics leaders must use the capabilities described in this guide to improve model reliability, trustworthiness, fairness, privacy and security. Sample vendors are provided.
Data Science and Machine Learning Trends You Can't Ignore.
Initiatives: Analytics, BI and Data Science Solutions
Data and analytics leaders should study this presentation to understand key trends influencing the future of ML and data science, such as AI engineering, MLOps, edge AI, federated ML, synthetic data and graph data science. They will learn about emerging ML capabilities and sample tools and vendors.
Life Science CIOs, Accelerate Clinical Development with New Applications of Artificial Intelligence.
Initiatives: Healthcare and Life Science Digital Optimization and Modernization
AI promises radical improvements in clinical trial efficiency, with notable early successes, yet fear, uncertainty and doubt among business and IT users slows acceptance and adoption. CIOs can use this research to demystify AI and identify the right approaches to ensure successful AI initiatives.
Top Strategic Technology Trends for 2023: AI Trust, Risk, and Security Management.
Initiatives: Artificial Intelligence
Artificial intelligence requires new forms of trust, risk and security management, yet organizations investigate these mainly to comply with regulations. IT leaders must change their approach, adopting AI TRiSM to protect their organizations and improve their business outcomes from AI models.
Top Strategic Technology Trends for 2023.
Initiatives: Digital Future
Thriving in times of intense economic and social volatility requires organizations to find new forms of efficiency in their operations, scale their productivity and pioneer new business models. IT leaders and other executives must use our trends to enable their organizations to succeed.
Emerging Tech Impact Radar: Artificial Intelligence.
Initiatives: Emerging Technologies and Trends Impact on Products and Services
Cool Vendors in AI Governance and Responsible AI — From Principles to Practice.
Initiatives: Artificial Intelligence
Data and analytics leaders must understand responsible AI and the measurable elements of that hierarchy — bias detection and mitigation, explainability, and interpretability. Supporting these practices facilitates understanding, trust and performance accountability required by stakeholders.
Innovation Insight for Bias Detection/Mitigation, Explainable AI, and Interpretable AI.
Initiatives: Artificial Intelligence
Growing adoption of artificial intelligence is forcing organizations to adopt practical approaches that resonate with their business and industry. Tools for AI safety, privacy, compliance, explainability, assurance and AI for good are increasingly available to data and analytics leaders.
Disclaimer.
Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
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