Current topics, practical solutions, and fresh ideas: On the HMS blog, you'll learn how companies successfully use data and analytics.
Explainable AI for Time Series Forecasts: Making Forecasts Explainable with SHAP
The article explains how Explainable AI makes time-series forecasts easier to understand. Using SHAP scores, forecasts are broken down into individual contributions, revealing the factors driving a forecast. The article also shows how forecast revisions between two forecast runs can be explained.
Erklärbare KI (XAI): Warum sie entscheidend für Vertrauen, Compliance und Business Impact ist
Erklärbare KI (XAI) macht KI-Entscheidungen nachvollziehbar und stärkt Vertrauen in automatisierte Systeme. Gleichzeitig unterstützt sie Compliance-Anforderungen wie den EU AI Act und sorgt dafür, dass KI in der Praxis wirklich genutzt wird.
How Do Companies Choose the Right Technology Partner? A Guide for CIOs
Choosing the right technology partner is a strategic decision for CIOs today. Learn which criteria really matter—from use-case fit to governance to implementation expertise.
Non-Generative AI Agents: When Classical AI Is Superior to Generative Models
The article explains when non-generative AI agents should be used and why traditional models remain superior to LLMs in many business-critical applications.
How can critical changes in the condition of intensive care patients be detected early and, at the same time, evaluated in a medically sound manner? A recent scientific paper published in *Communications Medicine*, a peer-reviewed journal in the Nature portfolio, addresses this question. Markward Britsch, a data scientist at HMS, was also involved in the work as part of an interdisciplinary research team.
