Artificial intelligence and machine learning-driven advancements in gastrointestinal cancer: Paving the way for precision medicine

Table 1 Historical evolution of artificial intelligence applications in gastrointestinal cancer management[5,46-48,123,173-175]

Year	Ref.	Country	Focus area	AI technique used	Dataset/study design	Key findings	Clinical impact/advancement
2015	Miyaki et al[173]	Japan	Early gastric cancer	SVM	100 cases (retrospective)	Achieved 84.6% accuracy in distinguishing EGC using blue-laser imaging	Demonstrated feasibility of ML in endoscopic analysis
2017	Hirasawa et al[46]	Japan	Gastric cancer detection	CNN (SSD architecture)	13584 images (retrospective)	92.2% sensitivity in detecting gastric cancer from endoscopic images	Validated AI’s potential for real-time lesion detection
2018	Luo et al[47]	China	Upper GI cancer screening	GRAIDS (CNN-based)	844424 cases (prospective)	95.5% diagnostic accuracy for upper GI cancers in real-time endoscopy	First real-time AI system for mass screening
2019	Zhu et al[48]	China	Invasion depth prediction	CNN (ResNet50)	993 images (retrospective)	89.16% accuracy in predicting gastric cancer invasion depth via endoscopy	Enhanced preoperative staging accuracy
2020	Nagao et al[174]	Japan	Metastasis prediction	ResNet50	16557 images (retrospective)	94.5% accuracy in identifying lymph node metastasis from CT images	Improved non-invasive metastasis assessment
2021	Hu et al[175]	China	Tumor margin delineation	VGG-16	694 images (retrospective)	82.7% accuracy in differentiating EGC margins under magnifying endoscopy	Supported precise endoscopic resection planning
2022	Wu et al[125]	China	Survival prediction	VGG-16, ResNet-50	100 videos (prospective)	78.57% accuracy in predicting survival and invasion depth in real-time EGD	Reduced diagnostic time by 90% compared to experts
2024	Mukherjee et al[5]	Global	Comprehensive review	ML/DL models	Meta-analysis of 50 + studies	Highlighted AI’s role in early detection (AUC: 0.86-0.94 across modalities)	Synthesized evidence for AI-driven personalized care

AI: Artificial intelligence; GI: Gastrointestinal; ML: Machine learning; DL: Deep learning; SVM: Support vector machine; CNN: Convolutional neural network; SSD: Single-shot detector; GRAIDS: Gastrointestinal artificial intelligence diagnostic system; VGG-16: Visual geometry group 16; EGC: Early gastric cancer; CT: Computed tomography; EGD: Esophagogastroduodenoscopy; AUC: Area under the curve.