
In this case study we demonstrate how you can use DIAL eXpressive Logic (XL) to uncover patterns and relationships in clinical trial data using natural language, all while keeping human in the loop. 

We loaded a sample clinical trial dataset of 1,000 patients into DIAL XL to investigate the hypothesis that the treatment group may influence the frequency of adverse events or study dropout in a gender-specific way. Additionally, we aimed to assess whether certain vital sign statistics, such as blood pressure and cholesterol levels, are associated with adverse events or study dropout across different treatment groups and genders. 

In this case study, DIAL XL's AI agents perform several tasks based on natural language prompts from the user:

- The AI agent interprets a query from a user, identifies the relevant dataset columns (e.g., gender, treatment group), generates a worksheet with the requested data, and provides a summary of key findings.
- Further, it creates a table, grouping patients by drug and calculate adverse effect frequencies.
- The agent focuses on patients with adverse effects, generates an intermediate table, and summarizes their blood pressure readings.
- The agent constructs tables and charts to visualize patterns in dropout rates and their correlation with adverse effects.

At every step, DIAL XL provided transparency by generating the underlying formulas, explaining the processes, and offering suggestions for next steps. This allowed users to review, validate, and refine the analysis—ensuring human oversight and control.

Solutions like DIAL XL are transforming clinical data analysis by enabling researchers to uncover hidden patterns, generate actionable insights, and streamline workflows—all in a faster, more efficient, and user-friendly way. Researchers can also create reusable templates to analyze different datasets to discover trends and validate hypotheses. 


Use DIAL eXpressive Logic (XL) AI-powered work-with-your-data platform with a natural language interface to streamline research, uncover hidden patterns and correlations in clinical trials.

Clinical Trials


In this case study we demonstrate how you can use DIAL to create multi-agent applications to work with scientific data on the example of OMICS dataset.

We created Omics AI Assistant that includes several agents handling tasks such as data query, visualization and analysis.

Key highlights:

- **Conversational Interface:** Researchers interact with the system through the DIAL Chat interface powered by language models, enabling intuitive information retrieval and analysis.
- **Versatile Knowledge Representation:** Discovered knowledge is presented in various formats like dynamic charts, tables, markdown, and visualizations, serving diverse analytical needs.
- **Knowledge Sharing:** The DIAL platform facilitates collaboration by enabling easy sharing of knowledge representations, effectively bridging knowledge gaps in an organization.

You can use DIAL platform to create multi-agent applications such as Omics AI Assistant help conduct open-ended analysis and exploration of data to uncover patterns, trends, and anomalies that can lead to new insights and hypotheses.
    

Enable research by allowing users to easily query and analyze vast amounts of scientific data using just natural language. Learn how we used our OMICS AI assistant to identify genes with the largest deviations in expression levels across multiple probes.

OMICS AI Assistant


This case study demonstrates how you can use DIAL to make your life as a researcher easier by turning complex scientific articles (even a combination of them) into intuitive and user-friendly knowledge graphs.

In this example, we used DIAL Mindmap to transform the Nature Cell Biology article ["Caspase-2 is a condensate-mediated deubiquitinase in protein quality control"](https://www.nature.com/articles/s41556-024-01522-8) into a visual knowledge graph.

It breaks down the provided data into logical and hierarchical structure, connects key concepts and ideas, provides summaries and useful information with links to the original sources.

Key benefits:

- Scientists can quickly navigate the ever-growing universe of scientific articles using knowledge graphs enriched with logical connections, summaries and references to sources.
- Researchers can quickly grasp complicated topics (in our case it is the protein quality control and its connection to diseases such as neurodegeneration). 
- Presenting information in a simplified visual format accelerates the process of identifying key insights and actionable solutions (in our case it is potential targets for treating cellular health disorders).
  

Accelerate exploration of ever-expanding world of scientific literature by turning complex articles into intuitive knowledge graphs. Learn how we used DIAL Mindmap to build a knowledge graph for the article about the role of Caspase-2 in protein quality control from Nature Cell Biology.

Caspase-2 Article Visualization


As a leader in global digital healthcare, Altera Digital Health consistently strives to enhance the patient experience by integrating cutting-edge technology. In [partnership with DIAL](https://www.linkedin.com/posts/ben-scharfe-cpa-52241968_dial-aiinaction-onepatientatatime-activity-7304197301860737024-dBxL?utm_source=social_share_send&utm_medium=member_desktop_web&rcm=ACoAAAxF6hwB7le9mPs0OW6sMCyf2-wHyDxK5gM), Altera leverages AI and other advanced technologies to achieve this goal.

This case study describes the Virtual Medical Assistant called Altera AI Note powered by DIAL that Altera created for their TouchWorks EHR platform.

Key highlights:

- **Voice recognition:** The Altera AI Note records a session of a doctor with a patient in real time. This information gets turned into the text and sent to DIAL.

- **Text Processing:** DIAL uses the selected language model and a specific predefined prompt to generate information for a doctor based on the provided transcript of the session.

As a result, the doctor receives a pre-populated medical session documentation and diagnosis recommendations. This reduces up to [15 minutes of time per patient every day](https://x.com/AlteraHealth/status/1826607065499836792). 


Develop AI-driven agents that enable EHR by automatically processing medical sessions and generating diagnosis recommendations for doctors, which significantly reduces the time doctors spend on each patient.

Virtual Medical Assistant


**Bring Personalized and Preventive Care to the Next Level with Generative AI**

Develop specialized applications that enhance the efficiency of repetitive manual tasks performed by doctors, while also paving the way for more personalized and preventive patient care.

**1. Preventive Care and Pattern Recognition**

Language models can process vast amounts of patient data—such as medical histories, genetic profiles, clinical trials, signals from wearable devices —to uncover patterns that humans might miss.  For instance, analyze biomarkers and symptoms to flag early warning signs of diseases , offering actionable insights to healthcare providers.

**2. Personalized Treatment**

Generative AI applications can help create highly personalized treatment plans. By analyzing a patient’s genetic makeup, past treatment responses, and lifestyle factors, AI-powered tools can recommend targeted therapies or medications. For instance, a GenAI app could estimate how a patient might respond to different drug regimens, enabling doctors to make more informed decisions tailored to that individual.

**3. Real-Time Monitoring and Alerts**

AI-powered applications are transforming patient monitoring by integrating data from wearables, medical devices, and EHRs. For example, an app can continuously analyze heart rate, glucose levels, or blood pressure and send real-time alerts to healthcare providers or patients when anomalies are detected. These systems ensure timely interventions, reducing the risk of complications.
        

Create AI-powered solutions that can help turn multi-format medical records into actionable insights for doctors, enhance preventive care by helping detect anomalies early based on diagnostic data, and generate personalized treatment plans.

Personalized & Preventive Care


Create AI-powered apps to manage clinical documentation, making it faster, more accurate, and less labor-intensive.

**1. Automating Clinical Records Processing**

AI-powered agents can aggregate and process lengthy medical records from various sources and formats, including electronic health records (EHRs), scanned documents, handwritten notes, and audio files eliminating the need for manual data entry, significantly reducing errors and saving time.

**2. Generating Compliant Documents and Reports**

AI systems excel at creating essential medical documents and reports such as discharge summaries, referral letters, insurance claims, regulatory reports.

Leverage AI to ensure compliance by securely processing sensitive information and standardizing documentation formats to meet legal requirements such as HIPAA (Health Insurance Portability and Accountability Act) in the U.S., ICD (International Classification of Diseases) coding standards for accurate billing, and GDPR (General Data Protection Regulation) for secure data handling in Europe.

By streamlining workflows and automating compliance, AI minimizes regulatory risks and allows healthcare providers to focus more on patient care, improving both efficiency and quality in the healthcare system.
        

Create AI-powered agents to process clinical records from multiple sources and formats, extract key information, and automatically generate compliant documents and reports.

Streamlined Clinical Paperwork


Develop Generative AI (GenAI) apps to automate key tasks, minimize errors, ensure regulatory compliance, and reduce claim denials, enabling faster reimbursements from insurance providers.

**1. Information Retrieval and Processing**

AI-powered solutions can instantly retrieve, verify, and organize a patient’s insurance details from sources like insurance portals, EHRs, or scanned cards, ensuring accurate and accessible information. This streamlines insurance verification by eliminating manual data entry, reducing errors, and saving time

**2. Paperwork Compliance and Automation**

GenAI tools simplify insurance processes by automatically generating claims and invoices while assigning accurate ICD and CPT codes for diagnoses and treatments. They ensure regulatory compliance and help avoid delays or rejections by flagging issues like missing documentation or invalid codes.
        

Build GenAI solutions that can retrieve patient’s insurance details, apply correct codes, and automatically generate invoices and pre-populated claim forms, ensuring compliance and fewer denials from insurance providers.