Risk prediction and analysis of gallbladder polyps with deep neural network

Figures & data

Figure 1. Interactive visualization of disease prediction models and gallbladder disease diagnosis.

Figure 2. GBNet model.

Table 1. Comparative experiments of different classification models oriented to the gallbladder categories change dataset.

Model	Accuracy	Precision	Recall	F1	AUC
LogisticRegression	0.848	0.609	0.720	0.647	0.837
DecisionTree	0.808	0.575	0.734	0.615	0.800
MultinomialNB	0.646	0.405	0.516	0.443	0.833
KNeighbor	0.606	0.407	0.497	0.444	0.650
GradientBoosting	0.838	0.550	0.653	0.585	0.873
Xgbc	0.859	0.617	0.724	0.656	0.800
RandomForest	0.879	0.616	0.603	0.608	0.877
AdaBoost	0.818	0.622	0.675	0.628	0.806
GaussianNB	0.828	0.627	0.679	0.634	0.85
GBNet	0.907	0.852	0.891	0.868	0.930

Figure 3. Normalized confusion matrix.

Figure 4. PR curve and ROC curve.

Figure 5. Visualization of the influence of physiological characteristics on the occurrence of lesions in the gallbladder.

Table 2. Correlation analysis of physiologic features affecting carcinogenesis of the gallbladder.

variable	benign polyp	gallbladder adenoma	gallbladder cancer	P_value
Gender(male/female)	149/138	8/7	13/12	0.925
Age	44.68 ± 11.624	47.60 ± 13.287	61.30 ± 11.835	<0.001
Weight	66.46 ± 12.001	68.13 ± 11.103	61.41 ± 10.252	0.086
Height	165.103 ± 7.5767	165.533 ± 6.7809	161.407 ± 7.5256	0.049
BMI	24.2707 ± 3.3526	24.8097 ± 3.2924	23.5463 ± 3.5296	0.450
Hypertension(Y)	44	5	10	0.005
Diabetes(Y)	22	1	4	0.425
HBV(Y)	51	5	1	0.045
Core antibody(Y)	134	1	5	<0.001
E antibody(Y)	68	3	4	0.116
TC	4.67 ± 0.971	4.94 ± 0.818	4.709 ± 0.837	0.551
TG	1.50 ± 1.304	1.335 ± 0.557	1.177 ± 0.644	0.310
HDL	3.98 ± 9.537	1.258 ± 0.227	1.260 ± 0.287	0.938
LDL	3.98 ± 17.996	3.189 ± 0.807	3.069 ± 0.805	0.952
FBG	5.03 ± 1.130	5.556 ± 1.055	5.531 ± 1.190	0.026
Uric acid	351.620 ± 98.507	347 ± 85.276	319.581 ± 93.271	0.268
Number of polyps(multiple)	163	2	4	<0.001
Polyp size	5.41 ± 3.699	9.86 ± 4.745	21.26 ± 10.589	<0.001
Wall thickness	2.933 ± 1.484	2.46 ± 1.024	6.74 ± 4.005	<0.001
MS(Y)	56	2	6	0.784
Gallbladder size(normal, enlarged, reduced)	273, 6, 8	12, 2, 1	12, 10, 5	<0.001
Symptoms(Y)	104	3	20	<0.001

Table 3. Binary logistic regression analysis of physiological characteristics influencing the development of carcinoma in the gallbladder.

variable	B	SE	Beta	t	P_value	95%CI(Low)	95%CI(Up)	Exp(B)
Gender(male)	−0.026	0.062	−0.023	−0.422	0.673	−0.148	0.096	0.974
Age	0.005	0.002	0.116	2.869	0.004	0.002	0.009	1.005
Weight	−0.029	0.023	−0.590	−1.242	0.215	−0.074	0.017	0.971
Height	0.021	0.019	0.275	1.078	0.282	0.017	0.059	1.021
BMI	0.090	0.062	0.524	1.438	0.151	−0.033	0.212	1.094
Hypertension(Y)	0.069	0.057	0.046	1.214	0.226	−0.043	0.181	1.071
Diabetes(Y)	−0.087	0.084	−0.042	−1.044	0.297	−0.251	0.077	0.917
HBV(Y)	0.050	0.058	0.033	0.863	0.389	−0.064	0.163	1.051
Core antibody(Y)	−0.149	0.045	−0.128	−3.328	<0.001	−0.237	0.061	0.862
E antibody(Y)	0.042	0.031	0.050	1.368	0.172	−0.019	0.103	1.042
TC	0.010	0.022	0.017	0.469	0.640	−0.033	0.054	1.010
TG	−0.027	0.019	−0.059	−1.419	0.157	−0.065	0.011	0.973
HDL	0	0.002	−0.004	−0.126	0.900	−0.005	0.004	1
LDL	−0.001	0.001	−0.022	−0.624	0.533	−0.003	0.002	0.999
FBG	0.021	0.020	0.043	1.081	0.281	−0.018	0.060	1.021
Uric acid	0	0	0.001	0.028	0.977	0	0	1
Number of Polyps(multiple)	−0.033	0.041	−0.116	−3.235	0.001	−0.214	−0.052	0.968
Polyp size	0.045	0.003	0.499	13.329	<0.001	0.038	0.051	1.046
Wall thickness	0.061	0.010	0.224	6.152	<0.001	0.042	0.081	1.063
MS(Y)	−0.038	0.066	−0.026	−0.574	0.567	−0.167	0.092	0.963
Gallbladder size(normal, enlarged, reduced)	0.276	0.046	0.218	5.951	<0.001	0.185	0.367	1.317
Symptoms(Y)	0.788	0.376	0.668	2.094	0.037	0.047	1.528	2.199
Constant	−4.313	3.205		−1.346	0.179	−10.620	1.994	0.013