J-J Liang - research works

Its development is limited by the lack of suitable training resources and the current performance of microsurgical robotic systems.

Here, we present the Microsurgical Silicone Tube Anastomosis dataset (MSTA), a large-scale 4 K video dataset of 0.2-mm silicone tube anastomosis procedures.

The participants represented a wide range of experience levels, with completion times ranging from 125 to 600 seconds, providing a broad spectrum of technical performance for analysis.

In addition, the dataset contains 47,452 segmentation annotation surgical frames, supporting computer vision studies.

Fusion transcripts were identified in 145 of 153 tumours (94.8%).

Fibrosarcomatous DFSP showed larger size and higher Ki-67 index than conventional DFSP (5.1 vs 4.1 cm, P = 0.023; 23.4% vs 9.1%, P < 0.001).

Among 122 patients followed after MMS, five relapsed (4.1%).

Ki-67 ≥ 15% strongly correlated with fibrosarcomatous change.

A and F indices increased with inflammation grade and fibrosis stage, respectively (p < 0.01).

SHAP analysis identified the dual elastography indices collectively as the dominant predictors.

An online risk calculator was developed from this model.