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Case Study: Turning Doctor Transcripts into Temporal Medical Record Knowledge Graphs

Case Study: Turning Doctor Transcripts into Temporal Medical Record Knowledge Graphs

Showcase of Data Transformation Process, Breakdown of 25 dev hours involved, Schemas used, Questions & Responses, and Graph created
Go to the profile of Chia Jeng Yang
Chia Jeng Yang
Leveraging Knowledge Table for CSV Medical Data Cleaning

Leveraging Knowledge Table for CSV Medical Data Cleaning

Data Cleaning of Tabular data through Knowledge Table, both as a Developer or as a Business User
Go to the profile of Chia Jeng Yang
Chia Jeng Yang
Rules, Extraction Guardrails, Knowledge Table & Studio

Rules, Extraction Guardrails, Knowledge Table & Studio

Knowledge Table Update: The 3 types of Guardrails & Rules for Automated & Human-In-The-Loop Extraction & Graph Creation
Go to the profile of Chia Jeng Yang
Chia Jeng Yang
Knowledge Table Making Extraction Cool Again (with Rules)

Knowledge Table Making Extraction Cool Again (with Rules)

Extraction Rules Dashboard, Data Processing of imported cells & UI Updates
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Chia Jeng Yang
Knowledge Table — Intelligent Chained Extraction through ‘Split Cell into Rows’

Knowledge Table — Intelligent Chained Extraction through ‘Split Cell into Rows’

Making Semantically Aware Extraction and Graph Creation work well through Knowledge Table
Go to the profile of Chia Jeng Yang
Chia Jeng Yang
File Directory for large document RAG systems

File Directory for large document RAG systems

Document Metadata Generation, File Directory & Two-Step Information Retrieval Processes
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Chia Jeng Yang
Knowledge Table — Multi-Document RAG (Extraction & Memory)

Knowledge Table — Multi-Document RAG (Extraction & Memory)

An Open-Source tool for Tabular & Rule-Based Extraction for Graph Memory & Ontology-Based Querying
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Chia Jeng Yang
Dynamic Expert Feedback: KG RAG as a Two-Way Retrieval & Memory System vs One-Way Vector System

Dynamic Expert Feedback: KG RAG as a Two-Way Retrieval & Memory System vs One-Way Vector System

How up-to-date dynamic context requires feedback and schemas that allow structured communication between humans and LLMs.
Go to the profile of Chia Jeng Yang
Chia Jeng Yang
WhyHow.AI’s talk at the 3rd Annual Industrial AI Conference ‘24

WhyHow.AI’s talk at the 3rd Annual Industrial AI Conference ‘24

Tom Smoker, Co-Founder at WhyHow.AI, spoke in September 2024 at the 3rd Annual Industrial AI Conference about Multi-Agent Knowledge Graph…
Go to the profile of Chia Jeng Yang
Chia Jeng Yang
Legal Document RAG: Multi-Graph Multi-Agent Recursive Retrieval through Legal Clauses

Legal Document RAG: Multi-Graph Multi-Agent Recursive Retrieval through Legal Clauses

Multi-graph multi-agent systems for legal documents that recursively retrieves different clauses, footnotes and definitions
Go to the profile of Chia Jeng Yang
Chia Jeng Yang
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