Copyright: ©Author(s) 2026.
World J Gastroenterol. Apr 21, 2026; 32(15): 116105
Published online Apr 21, 2026. doi: 10.3748/wjg.v32.i15.116105
Published online Apr 21, 2026. doi: 10.3748/wjg.v32.i15.116105
Figure 5 Long short-term memory prediction results on capsule endoscopy sequences.
A: Forward prediction of bleeding frames, visualized in the natural progression toward the anus; B: Reverse prediction aligned in the opposite direction toward the stomach; C: Graph of long short-term memory (LSTM) forward prediction probabilities across a sequence, showing temporal variation in bleeding likelihood; D: Graph of LSTM reverse prediction probabilities, capturing prediction stability across the sequence.
- Citation: Kuo HY, Lee KH, Chou CK, Mukundan A, Karmakar R, Chen TH, Wang TL, Liu PH, Wang HC. Deep learning-enhanced prediction of small intestinal bleeding points using long short-term memory networks. World J Gastroenterol 2026; 32(15): 116105
- URL: https://www.wjgnet.com/1007-9327/full/v32/i15/116105.htm
- DOI: https://dx.doi.org/10.3748/wjg.v32.i15.116105