Table 1 Results of using ANNs for diagnostics and prognosis in acute surgical diseases

Acute appendicitis (AA)

Yoldaş et al. [23]

156

AA diagnostics

Sensitivity—100%, specificity—97.2%

Park and Kim [24]

801

AA diagnostics

The ANN proved to be more accurate in diagnosing AA (the accuracy of the three types of ANN—99.8%, 99.4%, 97.8%) than the Alvarado clinical scoring system (72.2%)

Reismann et al. [25]

590

AA diagnostics, prediction of a complicated course of the disease in pediatrics

The ANN has allowed a significant improvement of the accuracy of diagnosis (sensitivity 93%, specificity 67%), and complicated course of AA (sensitivity 95%, specificity 33%)

Park et al. [26]

667

AA diagnostics based on CT of patients with abdominal pains

The ANN showed good and very good diagnostic indicators of AA (accuracy > 90%)

Acute pancreatitis (AP)

Kazmierczak et al. [27]

254

Diagnosis of the AP by the level of pancreatic enzymes in the blood serum

Lipase level has the highest diagnostic accuracy (accuracy lipase—82%, serum amylase—76%, lipase + amylase—84%)

Pofahl et al. [28]

156

Predicting the hospitalization length

Sensitivity 75%, specificity 81% and accuracy 79%, but the ANN predictive capabilities do not differ from Ranson and APACHE II

Keogan et al. [29]

92

Predicting the hospitalization length based on CT and laboratory tests

The ANN showed the best predictive accuracy (AUC = 0.83 ± 0.05) compared to the Ranson (AUC = 0.68 ± 0.06; P < 0.02) and Balthazar (AUC = 0.62 ± 0.06; P < 0.003)

Halonen et al. [30]

234

Predicting the potential mortality

The ANN predictive capabilities (AUC = 0.847) differ from Ranson (AUC = 0.655), APACHE II (AUC = 0.817) and Glasgow (AUC = 0.536)

Mofidi et al. [31]

496

Identification of the AP severity and predicting lethal outcome

The ANN proved to be more accurate in diagnosing of the AP (ANN was more accurate than APACHE II and Glasgow in predicting:

AP severity—P < 0.05 and P < 0.01

Multiple organ failure P < 0.05 and P < 0.01

Lethal outcome—P < 0.05 and P < 0.05)

Andersson et al. [32]

139

Predicting the AP severity

The ANN proved to be more accurate (AUC = 0.92) in diagnosing of the severe AP in comparison with the logistic regression (AUC = 0.84, P = 0.03) and APACHE II (AUC = 0.63, P < 0.001)

Hong et al. [33]

312

Predicting the persistent (more than 48 h) organ failure

The ANN proved to be more accurate in predicting of the persistent organ failure (AUC = 0.96 ± 0.02) in comparison with the logistic regression (AUC = 0.88 ± 0.03, P < 0.001) and APACHE II (AUC = 0.83 ± 0.03, P < 0.001)

Fei et al. [34]

152

Predicting the severe AP associated with acute lung injury

The ANN proved to be more accurate (AUC = 0.859 ± 0.048) in predicting of the acute lung injury accompanying the AP in comparison with the logistic regression (AUC = 0.701 + 0.041)

Acute cholecystitis (AC)

Eldar et al. [35]

180

Predicting the conversion from laparoscopic to laparotomic access in AC

The ANN demonstrated a good predictive ability to predict the conversion from laparoscopic to laparotomic approach (100% of cases respectively, 67%—prospectively) and to determine the group of patients requiring laparotomic cholecystectomy

Vukicevic et al. [36]

303

Prediction of choledocholithiasis in patients with gallstone disease and AC

The ANN demonstrated a good predictive ability to predict the choledocholithiasis and revealed informative clinical, laboratory, and instrumental signs (sensitivity—82.3%, specificity—94.7%, accuracy—92.2%, and AUC—0.934 in the validation set)

Ulcerative bleeding

Rotondano et al. [37]

2380

Predicting the fatal outcome in patients with bleeding from the upper gastrointestinal tract

The predictive ability of the ANN is better than the score Rockall’s one [38] (sensitivity—83.8% versus 71.4%, specificity—97.5% versus 52.0%, accuracy—96.8% versus 52.9%, and AUC—0.95 versus 0.67)

Wong et al. [39]

22,854

Identification of patients with a high risk of recurrent bleeding requiring surgical treatment and with a high risk of death

The ANN demonstrated AUC = 0.78, and accuracy—84.3%

Perforated gastroduodenal ulcers

Søreide et al. [44]

117

Predicting the fatal outcome and determination of factors of the fatal outcome

AUC = 0.90, 0.95% CI [0.85–0.95]

Ileus/bowel obstruction

Cheng et al. [45]

13,935 X-ray pictures

Ileus diagnostics

Sensitivity—91.4%, specificity—91.9%

Strangulated hernia

Chen et al. [46]

762

Predicting the need for bowel resection

ANN revealed eight factors that are significantly associated with the need for bowel resection