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Medical AI

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DevOps
DevOps
Apr 20, 2025 · Artificial Intelligence

Building a Medical Knowledge Base with RAG: A Step‑by‑Step Example

This article demonstrates how to construct an AI‑powered medical knowledge base for diabetes treatment by preprocessing literature, performing semantic chunking, generating BioBERT embeddings, storing them in a FAISS vector database, and using a RAG framework together with a knowledge graph to retrieve and generate accurate answers.

BioBERTMedical AIRAG
0 likes · 12 min read
Building a Medical Knowledge Base with RAG: A Step‑by‑Step Example
DataFunSummit
DataFunSummit
Jul 16, 2024 · Artificial Intelligence

Knowledge Graph Construction, Reasoning, and QA for Intelligent Hypertension Diagnosis

This article presents a comprehensive exploration of knowledge‑graph‑based modeling, neural‑symbolic multi‑hop reasoning, and large‑model‑driven question answering applied to precise medication decision‑making in hypertension, detailing system architecture, experimental evaluations, real‑world deployments, and future research directions.

Medical AIhypertensionknowledge graph
0 likes · 26 min read
Knowledge Graph Construction, Reasoning, and QA for Intelligent Hypertension Diagnosis
DataFunTalk
DataFunTalk
Feb 24, 2024 · Artificial Intelligence

Challenges and Opportunities in Applying Large‑Scale AI Models to Healthcare

The article analyzes how large‑model AI is reshaping medical practice, highlighting rapid technology adoption but significant implementation hurdles due to physician behavior, data silos, safety regulations, talent gaps, and differing maturity across R&D, manufacturing, marketing, and customer‑service domains.

AI adoptionData ChallengesHealthcare Innovation
0 likes · 6 min read
Challenges and Opportunities in Applying Large‑Scale AI Models to Healthcare
DataFunTalk
DataFunTalk
Feb 23, 2024 · Artificial Intelligence

Challenges and Opportunities in Applying Large‑Model AI to Healthcare

The article analyzes how large‑model medical AI is rapidly adopted yet struggles with implementation due to doctor shortages, behavioral resistance, data silos, safety regulations, and the need for strategic alignment, while contrasting the more supportive innovation ecosystem in the United States.

AI adoptionHealthcare InnovationLarge Models
0 likes · 6 min read
Challenges and Opportunities in Applying Large‑Model AI to Healthcare
AntTech
AntTech
Dec 19, 2023 · Artificial Intelligence

RJUA‑QA: A Comprehensive Urology QA Dataset for Large Language Model Evaluation

RJUA‑QA is a newly released, large‑scale urology question‑answer dataset constructed from virtual patient records based on clinical experience, featuring 2,132 QA pairs with extensive context, designed to benchmark and improve large language models’ medical reasoning, diagnosis, and treatment recommendation capabilities.

Medical AIQA datasetUrology
0 likes · 12 min read
RJUA‑QA: A Comprehensive Urology QA Dataset for Large Language Model Evaluation
HaoDF Tech Team
HaoDF Tech Team
Sep 15, 2021 · Artificial Intelligence

Optimizing Question‑Answer Search Similarity in Haodf Online: A Semantic Similarity Model Case Study

This article describes how Haodf Online improved its medical question‑answer search by analyzing search challenges, adopting semantic similarity models based on pre‑trained language embeddings, designing contrastive training tasks, and evaluating the resulting increase in click‑through rate and user engagement.

Medical AINatural Language ProcessingSearch Relevance
0 likes · 12 min read
Optimizing Question‑Answer Search Similarity in Haodf Online: A Semantic Similarity Model Case Study
DataFunTalk
DataFunTalk
Aug 31, 2021 · Artificial Intelligence

Applying Knowledge Graphs for Clinical VTE Risk Assessment: A Case Study from HuiMei Technology

This article describes how HuiMei Technology leverages a medical knowledge graph, natural‑language processing, and AI‑driven scoring to automate venous thromboembolism (VTE) risk assessment in large hospitals, detailing the business background, technical architecture, implementation workflow, and ongoing research directions.

Medical AINatural Language ProcessingSNOMED-CT
0 likes · 16 min read
Applying Knowledge Graphs for Clinical VTE Risk Assessment: A Case Study from HuiMei Technology
DataFunTalk
DataFunTalk
Aug 24, 2020 · Artificial Intelligence

Short Text Understanding in the Medical Health Domain: Business Scenarios and Technical Practices

This presentation details the challenges and solutions for short‑text understanding in medical health, covering DingXiangYuan’s business scenarios, NLP pipeline components, knowledge‑graph construction, concept mining, and their impact on search, recommendation, and tagging systems.

Concept MiningMedical AINLP
0 likes · 19 min read
Short Text Understanding in the Medical Health Domain: Business Scenarios and Technical Practices
Tencent Cloud Developer
Tencent Cloud Developer
Aug 6, 2018 · Artificial Intelligence

Tencent's AI Breast Cancer Screening System: Technical Architecture and Implementation

Tencent's AI Breast System combines mammography, pathology, MRI and ultrasound analysis using a multi‑scale, progressive TMuNet model that processes four views, learns from physician feedback, and delivers lesion localization, malignancy scoring and automated reports, achieving up to 92% sensitivity and reducing annotation time.

AI Medical ImagingBreast Cancer DetectionComputer Vision
0 likes · 13 min read
Tencent's AI Breast Cancer Screening System: Technical Architecture and Implementation