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Methods proposed Performance analysis [30] Clinical applications Deep learning–based diagnosis Detects metastases in hematoxylin and eosin–stained tissue sections of lymph nodes of women with breast cancerAchieves 95% CI using 3-layer CNN [31] Clinical applications -Radiology Clinical decision-making using CNN Achieves 20% improvement over sonographer readings after training with ultrasound images of left and right carotid artery from 203 patients. [32–34] Clinical applications -survival prediction Probabilistic Neural NetworkMulti-layer PerceptronGene expression classifierSupport Vector MachineRadial Basis Neural NetworkK-means algorithm Trained with 23 demographic, tumor-related parameters and selected perioperative data from 102 patients.PNN achieves high prediction ability with an accuracy of 0.892 and sensitivity of 0.975 [35] Surgical Applications Rotational matrix and translation vector algorithm to reduce the geometric error Improves the video accuracy by 0.30–0.40 mm (in terms of overlay error)Enhances processing rate to 10–13 frames/sDepth perception is increased by 90–100 mm [36–38] Surgical Applications Feasibility of laparoscopic Sentinel Lymph Node (SLN) staging 245 SLN nodes were removed out of 370 lymph nodes from 87 patients.

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