Exploration of Digestive Diseases

Table 1. Example deep learning models and their interventional relevance.

Model name	Primary architecture/Type	Core clinical task	Relevant IR procedure/Application
ProgSwin-UNETR	Swin Transformer/DL	Longitudinal prognosis stratification	Monitoring HCC response after TACE
aHVPG Model	AutoML/CNN	Non-invasive prediction of HVPG (pressure gradient)	PHT diagnosis; TIPS candidacy
Swin-UNETR	CNN/Transformer Hybrid	3D segmentation of tumors and organs at risk	Y-90 dosimetry planning; ablation simulation
Neuro-Vascular Assist	Real-Time AI System	Real-time safety monitoring (detects migrating embolic agents)	Visceral or neuro-embolization
ChatGPT (GPT-4)	Large Language Model (LLM)	Statistical analysis and data interpretation	Accelerating clinical research and protocol design
K-Net/MobileViT	CNN/Transformer Hybrid (Dual-Stage)	High-accuracy segmentation and classification	Nodule/Lesion triage and feature analysis

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IR: interventional radiology; DL: deep learning; HCC: hepatocellular carcinoma; TACE: transarterial chemoembolization; ML: machine learning; CNN: convolutional neural network; HVPG: hepatic venous pressure gradient; PHT: portal hypertension; TIPS: transjugular intrahepatic portosystemic shunt; AI: artificial intelligence.

Declarations

Author contributions

HY: Conceptualization, Investigation, Writing—original draft, Writing—review & editing. The author read and approved the submitted version.

Conflicts of interest

The author declares that there are no conflicts of interest or competing financial interests to disclose.

Ethical approval

As this is a narrative review of previously published literature and does not involve original human or animal research, ethical approval from an Institutional Review Board (IRB) was not required.

Consent to participate

Not applicable.

Consent to publication

Not applicable; this manuscript does not contain individual patient data or identifying information.

Availability of data and materials

No new datasets were generated or analyzed during the preparation of this narrative review. All information presented is derived from cited, publicly available literature.

Funding

No external funding was received for this study.

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