Multitask learning in hepatocellular carcinoma: Integrating diagnosis, prognosis, and clinical decision support

Table 2 Study design, validation, and limitations of included multitask learning studies

Ref.	Primary task category	Sample size	Study design	Ext valid	Key study-level limitations
Zhao et al[55]	Diagnostic/biologic aggressiveness prediction	145	Retrospective multicenter study; 10-fold CV in center 1 + external independent test set from centers 2 and 3	Yes	Limited sample size; single-center training with potential inter-center domain bias; HBP-only model; no clinical-variable integration; no prospective validation
You et al[30]	Structural + diagnostic grading	1673	Retrospective single-center study; 80/10/10 train-validation-test split + five-fold CV	No	Single-center retrospective design; no external or prospective validation; arterial/portal-venous MRI only; clinical/genomic variables not integrated; sequential pipeline without demonstrated joint multitask optimization or shared-representation learning
Wang et al[52]	Prognostic survival prediction	2197	Retrospective SEER database study; 7:3 train/test split + five-fold CV	No	Registry-based design; no imaging data; no independent external validation; limited clinical granularity; black-box interpretability remains limited
Wang et al[51]	Biologic + prognostic + treatment-benefit prediction	725	Retrospective multicenter study; training/internal test split + three external test sets	Yes	Retrospective design; predominantly HBV-related Chinese cohort; moderate RFS performance in some external sets; nonrandomized PA-TACE benefit analysis; no prospective validation
Song et al[16]	Prognostic recurrence prediction	167 patients/765 CT slices; FLL classification: 85 CT volumes/489 slices	Retrospective single-center study; 10-fold CV for ER prediction + 5-fold CV for FLL classification	No	Small single-center HCC cohort; no external or prospective validation; ROI-based 2D slice analysis; multitask component limited to pre-training; method restricted to multi-phase CT images
Wen et al[36]	Structural + pathological differentiation prediction	295 patients/885 CE-MRI	Retrospective single-center study; train-test split + five-fold CV within the training set	No	Single-center design; no external or prospective validation; modest cohort size; simplified pathological differentiation categories
Xie et al[37]	Structural + biologic aggressiveness prediction	137	Single-institution study; random train/validation-test split	No	Small cohort; no external or prospective validation; limited MRI phase/sequence reporting; internal split only
He et al[18]	Biologic subtype + prognostic prediction	MTM cohort: 159; HAIC cohort: 752	Retrospective multi-institutional study; training/internal test cohorts from one institution + external test cohort from four centers	Yes	Retrospective design; MTM cohort mainly surgical; HAIC-only prognostic cohort; limited generalizability to other treatment contexts; no prospective validation; whole-liver ROI approach not compared with tumor-specific ROI; complications during and after HAIC or TKI treatment were not analyzed
Xiao et al[54]	Structural detection + quantitative assessment	135 subjects/10800 MRI slices	Single-dataset experimental study; five-fold CV	No	Small dataset; no external or prospective validation; single-source MRI dataset; protocol-specific multimodality inputs
Li et al[10]	Treatment response prediction + segmentation	248	Retrospective two-center study; training/internal validation cohort + external testing cohort	Yes	Retrospective design; two-center dataset; 2D-only network with limited spatial-context utilization; small DEB-TACE subgroup; no prospective validation
Li et al[40]	Biologic aggressiveness prediction + segmentation	85	Two-center study; internal CV in center 1 + external validation in center 2	Yes	Small HCC cohort; limited external cohort size; MRI phase/sequence reporting incomplete; no prospective validation
Chu et al[49]	Biologic aggressiveness prediction + prognostic stratification	133	Single-center retrospective cohort; 7:3 train/internal validation split	No	Limited sample size; single-center design; strict exclusion criteria; no external validation
Wang et al[53]	Pathology-based structural segmentation	PAIP: 100 HCC WSIs; CRAG: 213 images; UHCMC & CWRU: 110 images	Public benchmark-based experimental study; PAIP train/validation/test split + CRAG and UHCMC&CWRU train/test splits	No	HCC validation limited to PAIP; external benchmark datasets were non-HCC pathology images; pathology-only input; no prospective clinical validation
Fu et al[7]	Future macrovascular invasion prediction + survival stratification	366	Retrospective multicenter study; training dataset from four hospitals + external validation dataset from one hospital	Yes	Retrospective design; strict inclusion criteria; HBV-predominant Chinese cohort; no prospective validation; black-box interpretability remains limited
Liu et al[50]	Histologic surrogate prediction + post-TACE survival prediction	494 surgical cohort; 243 TACE cohort	Retrospective single-center study; surgical cohort for histologic-score development + TACE cohort for survival modeling	No	Survival model limited to TACE-treated patients; retrospective design; no external validation; complex multi-stage pipeline introduces risk of compounding overfitting; label reliability for histological surrogates not formally assessed
Huang et al[56]	Structural + biologic aggressiveness prediction	114 HCC samples	Single-center study; 4-fold CV repeated five times	No	Small single-center cohort; no external validation; slice-based analysis; IVIM parameter fitting evaluated indirectly using reconstructed b-value images

TACE: Transarterial chemoembolization; IVIM: Intravoxel incoherent motion; MVI: Microvascular invasion; CT: Computed tomography; CE-MRI: Contrast-enhanced magnetic resonance imaging; MTM: Macrotrabecular-massive; HAIC: Hepatic arterial infusion chemotherapy; MRI: Magnetic resonance imaging; PAIP: Pathology artificial intelligence platform; HCC: Hepatocellular carcinoma; WSI: Whole-slide image; CRAG: Computational pathology research group; UHCMC: University Hospitals Cleveland Medical Center; CWRU: Case Western Reserve University; CV: Cross-validation; SEER: Surveillance, Epidemiology, and End Results; ER: Early recurrence; FLL: Focal liver lesion; HBP: Hepatobiliary phase; HBV: Hepatitis B virus; RFS: Recurrence-free survival; PA: Postoperative adjuvant; ROI: Region of interest; 2D: Two-dimensional; 3D: Three-dimensional; CNN: Convolutional neural network.