ResearcherSichuan UniversityActive in the last 2 years

Ling Song

ORCID-verified (high confidence, 0.95), identity_conf@1As of 8 November 2026

Matched on ORCID iD 0000-0003-1597-4601; OpenAlex author ID A5082323913. Sources: OpenAlex.

Their work

Papers: 2
Trials: 0
Grants: 0
Labs led: 0
Collaborators: 5

Papers, trials and grants by year

2022: 1 paper · 2023: none · 2024: none · 2025: 1 paper

Papers 2

Impaired sleep efficiency predicts adverse prognosis in elderly pancreatic cancer patients: a retrospective case - control study based on wearable smart device… Co-author DOI 10.62347/sqss8531 ↗
Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis. Co-author DOI 10.1186/s12916-022-02258-8 ↗

Closest collaborators

The 5 strongest of 5 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

Jionghui Gu · 1 shared paper, 2022 · strength 0.14
- Paper Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenoc… DOI 10.1186/s12916-022-02258-8 ↗
Tong Tong · 1 shared paper, 2022 · strength 0.14
- Paper Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenoc… DOI 10.1186/s12916-022-02258-8 ↗
Tianan Jiang · 1 shared paper, 2022 · strength 0.14
- Paper Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenoc… DOI 10.1186/s12916-022-02258-8 ↗
Kun Wang · 1 shared paper, 2022 · strength 0.14
- Paper Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenoc… DOI 10.1186/s12916-022-02258-8 ↗
Jie Tian · 1 shared paper, 2022 · strength 0.14
- Paper Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenoc… DOI 10.1186/s12916-022-02258-8 ↗

How to reach this person

A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.