Table 7.

Radiotherapy and assessment of response to treatment with DL

Anatomic site	Object or task	Network input	Network architecture	Dataset (train/test)
Bladder	Treatment response assessment268	CT	CifarNet	82/41 patients
Brain	Glioblastoma multiforme treatment options and survival prediction218	MRI	Custom	75/37 patients
	Assessment of treatment effect in acute ischemic stroke269	MRI	CNN based on SegNet	158/29 patients
Breast	Response to neoadjuvant chemotherapy270	MRI	Pretrained VGGNet followed by LDA	561 examinations from 64 subjects LOO CV
	Response to neoadjuvant chemotherapy271	MRI	Custom	133/33 patients
	Segmentation of clinical target volume272	CT	Deep dilated residual network	800 patients fivefold CV
Cancer cell lines	Prediction of drug effectiveness in cancer cell lines273	Multiple omics data from cancer cells (gene expression data, copy number variation data, mutation data, and cell line annotations)	Deep autoencoder	520/104 cell lines
Head and Neck	Organ segmentation274	CT	U‐Net based with shape retention model	22/10 scans
Kidney	Renal segmentation275	CT	Custom	89/24 patients
	Early detection of acute renal transplant rejection276	DWI‐MRI	Stacked autoencoders	100 patients fourfold, tenfold and LOO CV
Liver	Hepatobiliary toxicity prediction after liver SBRT277	CT and patient demographics, clinical information	Custom CNN trained on other organs, fine‐tuned on liver SBRT	125 patients 20‐fold CV
Lung	Estimation of dose protocols in Radiotherapy278	FDG‐PET/CT, clinical, genetic, imaging radiomics features, tumor and lung dosimetric variables, treatment plans	Deep Q‐Network	114 real train/4000 synthesized test cases
	Dynamic tracking during therapy279	DRRs from 4D CT	DenseNet	1/9 volumes
Prostate	Prediction of dose from patient image contours280	IMRT	U‐net	80/8 patients
	Prediction of dosimetric eligibility of prostate cancer patients undergoing IMRT281	CT	Fine‐tuned AlexNet	60 patients fivefold CV
Pelvis	Generating synthetic CTs from MR‐only radiotherapy282	MRI	CGAN	123/59 patients
	Assessment of toxicity to normal organs and tissue283	Rectum surface dose maps	Fine‐tuned VGG‐16	42 patients tenfold and LOO CV
Rectum	Segmentation of rectal tumors on T2‐MRI and clinical target volume segmentation on CT272	T2‐MRI or CT	Novel CNN involving cascaded atrous convolution and spatial pyramid pooling	70 T2‐MR and 100 CT fivefold CV
	Prediction of pathologic complete response after chemoradiation284	CT	DNN classifier custom estimator	95 patients fivefold CV

IMRT, intensity‐modulated radiation therapy; SBRT, stereotactic body radiotherapy; DWI, diffusion‐weighted MRI; DRR, digitally reconstructed radiographs; LDA, linear discriminant analysis; LOO, leave‐one‐out; CV, cross‐validation.