Fig 1.
Content reconstruction diagram.
Horizontal teaching refers to a modular approach, whereas vertical teaching alludes to a chain methodology.
Fig 2.
Prerequisites, human-computer interaction, and feedback optimization.
Table 1.
Details of the developed techniques.
Fig 3.
The AI assistant is represented by an icon of a small monkey.
Fig 4.
Each box represents a scene module. Blue arrows depict the patient’s route, while yellow arrows denote the nuclear medicine technologist’s pathway.
Fig 5.
Virtual interface of the hall.
The patient remains in the waiting hall, which is equipped with waiting desks and landmarks.
Fig 6.
The pre-examination preparation room.
In the image, a yellow call button is located on the left side of the consultation desk, while a weighing scale is situated on the right side.
Fig 7.
The lead box, containing the radioactive drug, is situated on one side, while the patient waits on the opposite side of the lead protective cover for injection with the medication.
Fig 8.
(A) The patient is entering the waiting room. (B)The patient is sitting in the waiting chair and waiting to be called.
Fig 9.
Nuclear medicine technologists conduct image acquisition on patients by remotely operating the equipment from within a shielded compartment.
Table 2.
The seven major inspection details.
Fig 10.
The examination procedure comprises eight stages: Introduction to the Principle--Calling the Number--Medical History Collection--Weighing--Injection in the Injection Room (required for static collection)--Calling the Number--Positioning (for dynamic collection, an additional bedside medication step is needed)--Image Collection.
Table 3.
Details of teaching practice.
Table 4.
Details of pre-class test and post-class test.
Fig 11.
Pre-class and post-class test.
The pre-class test and post-class test quantify the students’ performance before and after utilizing the online practical training platform, respectively. A: Pre-class test scores; B: Post-class test scores.
Table 5.
Results of training and assessment mode.
Fig 12.
Overall sample performance distribution.
The dispersion of student grades across 272 total samples for the 2023-2024-2 and 2024-2025-2 academic year’s second semesters is detailed.A: First training result.B:Multiple training average.C:Assessment results.
Fig 13.
Individual sample grade distribution.
Three distinct samples were arbitrarily chosen for examination. The horizontal axis indicates the frequency of training sessions, while the vertical axis denotes performance. A: Sample 1.B:Sample 2.C:Sample 3.
Fig 14.
The effect of training frequency.
The horizontal axis represents the number of training sessions, while the vertical axis represents the assessment results.
Fig 15.
Different colors denote varying degrees of satisfaction.