Artificial intelligence in gastrointestinal diseases

Table 1 Classification of systems in artificial intelligence-oriented disease management

Disease of interest	Purpose of AI	User	Limitation of use	Ref.
Acute appendicitis	Diagnosis	Specialist	The study is designed in retrospective nature	Reismann et al[5]
Colon cancer	Diagnosis	Specialist	The design of the analysis is post hoc and the number of patients is limited	Reichling et al[6]
Ulcerative colitis	Diagnosis	Specialist	Long-term clinical prognosis is not clear	Maeda et al[7]
Spinal stenosis in degenerative lumbar kyphoscoliosis	Surgery navigation	Specialist	The number of patients is limited. Long-term follow-up data is needed	Ho et al[9]
Coronavirus infectious disease (COVID-19)	Screening, diagnosis	Specialist	Privacy of the patient data should be considered	Bhattacharya et al[10]
Diseases in general	Diagnosis	Specialist	The burden on specialists may increase	Karako et al[11]
Diseases in general	Screening	Specialist	Careful and thorough investigation is necessary	Shiyam Sundar et al[12]
Gastrointestinal disease	Diagnosis	Specialist	There is a difference in the definition of anomaly detection between the area of computer science and medical domain	de Lange et al[13]
Gastrointestinal disease, hepatic diseases	Diagnosis	Specialist	High-quality datasets are needed	Le Berre et al[14]
Colorectal cancer	Diagnosis	Specialist	The quality of previous study designs is limited, and practical usefulness of computer-associated diagnosis systems is unknown	Kudo et al[15]
Colorectal cancer, bladder cancer	Prediction of anti-cancer drug efficacy	Specialist	Further molecular layer profiling in organoids may be needed	Kong et al[17]
Hypopharyngeal squamous cell carcinoma, esophageal squamous cell carcinoma	Identification of diagnostic and therapeutic targets	Specialist	Further studies are needed to validate the findings of the study	Zhou et al[18]
Arterial stenosis, coronary arterial diseases, stricture of the gastrointestinal tract	Guiding of balloon catheter	Specialist	The systemic performance needs to be improved	Kim et al[19]
Gastrointestinal disease	Diagnosis	Specialist	Further studies are needed to improve the performance	Marlicz et al[20]
Colorectal cancer	Prediction of liver metastasis	Specialist	The investigation of another dataset is needed	Lee et al[21]
Colon cancer	Diagnosis	Specialist	The change of protein expression level needs to be investigated	Xue et al[22]
Gastrointestinal disease	Diagnosis	Specialist	Investigation and development of newly improved methods are encouraged	Borgli et al[23]
Gastrointestinal disease	Diagnosis	Specialist	Further development is needed	Adler and Bjarnason[24]
Upper gastrointestinal cancer	Diagnosis	Specialist	Only high-quality endoscopic images for the training and validation analyses were used	Luo et al[25]
Gastric cancer	Diagnosis	Specialist	The associations of the quality or the number of training images and the CNN accuracy needs to be examined	Hirasawa et al[26]
Gastrointestinal disease	Diagnosis	Specialist	The possibilities to improve the medical performance, to reduce the medical cost, and to improve the satisfaction of the patient and medical staff are unknown	Min et al[27]
Functional gastrointestinal disorder	Diagnosis	Specialist	Evaluation of the feasibility of AI on studies on the gut-brain-microbiome axis is needed	Mukhtar et al[28]
Colorectal cancer	Diagnosis	Specialist	The uncertainty about the true efficacy of CAD in “real-world” practice remains	Ahmad et al[29]
Colorectal cancer	Diagnosis	Specialist	Further accumulation of lesion images for training is needed	Yamada et al[30]
Small-bowel disease	Diagnosis	Specialist	Further multicenter, prospective studies and external validation are needed	Yang[31]
Colorectal cancer	Diagnosis	Specialist	Complaints of system malfunctions and reports of patient injuries could lead to lawsuits against stakeholders	Ciuti et al[32]
Cholangiocarcinoma, pancreatic adenocarcinoma	Diagnosis	Specialist	Case-control and single-center design, and the lack of an independent validation cohort should be considered	Urman et al[33]
Colorectal cancer	Screening	Specialist	The applicability to other types of cancer needs optimization	Misawa et al[34]
Gastrointestinal disease	Diagnosis	Specialist	Most studies were designed in retrospective manner. Ethical issues on misdiagnosis or misclassification need to be handled	Yang and Bang[35]
Gastrointestinal cancer	Prediction of microsatellite instability for immunotherapy	Specialist	Larger training cohorts are needed	Kather et al[36]
Colorectal cancer	Diagnosis	Specialist	The CNN architecture needs to be improved for colonoscopy	Azer[37]
Barrett esophagus cancer	Diagnosis	Specialist	The number of patients is limited. Further optimization is needed	Ebigbo et al[38]
Celiac disease	Diagnosis	Specialist	The preliminary results need to be followed-up with a real clinical setting	Tenório et al[39]
Esophageal squamous cell carcinoma	Prediction of prognosis	Specialist	Further experimental studies to verify the results are needed	Zhang et al[40]
Advanced rectal adenocarcinoma	Prediction of response to neoadjuvant chemoradiotherapy	Specialist	The size of the cohort is limited. The confirmation of the findings with another data set is needed	Ferrando et al[41]
Inflammatory bowel disease	Prediction of prognosis	Specialist	Interventional study to confirm the efficacy of the stratifying therapy is needed	Biasci et al[42]
Inflammatory bowel disease	Mapping	Specialist	The application of advanced natural language processing algorithms to the text-mining step may improve the current process	Sarntivijai et al[43]

AI: Artificial intelligence; CAD: Computer-aided diagnosis; CNN: Convolutional neural network.