Graph models have emerged as a pivotal framework in the analysis of strategic conflicts and the development of decision support systems.

Large language models (LLMs) have proven capable of assisting with many aspects of organizational decision making, such as helping to collect information from databases and helping to brainstorm ...

Here, we aimed to develop and validate a decision support system to define the optimal timing of HSCT for patients with MDS on the basis of clinical and genomic information as provided by the ...

Mass General Brigham researchers see value in a hybrid approach that makes use of generative artificial intelligence to diagnose patients. Comparing two large language models (LLMs) – OpenAI's GPT-4 ...

From Rule-Based To Personalized For decades, clinical decision support systems have relied on static, rule-based algorithms.

This growth is fueled by surging demand for improved clinical outcomes, reduced medication errors, and seamless integration of decision support tools into electronic health record (EHR) systems.

The technology company MultiCare chose proposed a clinical decision-support system that would be quietly present at the moment of clinical decision-making, offering evidence-based options when ...

Left to their own devices, model outputs are commonly documented as reflecting bias or offering plausible but incorrect information. Productive collaboration between AI and human decisionmakers will ...

A Race-Aware Approach To Clinical Decision Support The inclusion of race and ethnicity in algorithms is problematic when it perpetuates the false notion that race is a biological construct.