A modified U-net with graph representation for dose prediction in esophageal cancer radiotherapy plans.

The manual design of esophageal cancer radiotherapy plan is time-consuming and labor-intensive. Automatic planning (AP) is prevalent nowadays to increase physicists' work efficiency. Because of the intuitiveness of dose distribution in AP evaluation, obtaining reasonable dose prediction provides effective guarantees to generate a satisfactory AP.

Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears.

Technical advancements significantly improve earlier diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various factors. We develop an artificial intelligence assistive diagnostic solution, AIATBS, to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria. We train AIATBS with >81,000 retrospective samples.

The Role of Phonological Processing in Semantic Access of Chinese Characters: A Near-Infrared Spectroscopy Study.

The Stroop task was used to investigate the role of phonological processing in semantic access for written Chinese language. Fourteen children were recruited to perform the Stroop task, using color characters, their homophones and neutral characters as stimuli. Near-infrared spectroscopy (NIRS) was used to measure the brain activation in the prefrontal cortex (PFC) during the task.