activity
20192022
most citedQuantification of Robotic Surgeries with Vision-Based Deep Learning

2 citations · 2 across the 4 of their papers we have counts for

collaborators

7 papers

cs.RO20222 cited

Quantification of Robotic Surgeries with Vision-Based Deep Learning

Dani Kiyasseh, Runzhuo Ma, Taseen F. Haque +4

Surgery is a high-stakes domain where surgeons must navigate critical anatomical structures and actively avoid potential complications while achieving the main task at hand. Such s…

cs.CL2021

Let Your Heart Speak in its Mother Tongue: Multilingual Captioning of Cardiac Signals

Dani Kiyasseh, Tingting Zhu, David Clifton

Cardiac signals, such as the electrocardiogram, convey a significant amount of information about the health status of a patient which is typically summarized by a clinician in the…

eess.SP2020

PCPs: Patient Cardiac Prototypes

Dani Kiyasseh, Tingting Zhu, David A. Clifton

Many clinical deep learning algorithms are population-based and difficult to interpret. Such properties limit their clinical utility as population-based findings may not generalize…

eess.SP2020

CROCS: Clustering and Retrieval of Cardiac Signals Based on Patient Disease Class, Sex, and Age

Dani Kiyasseh, Tingting Zhu, David A. Clifton

The process of manually searching for relevant instances in, and extracting information from, clinical databases underpin a multitude of clinical tasks. Such tasks include disease…

cs.LG2020

SoQal: Selective Oracle Questioning in Active Learning

Dani Kiyasseh, Tingting Zhu, David A. Clifton

Large sets of unlabelled data within the healthcare domain remain underutilized. Active learning offers a way to exploit these datasets by iteratively requesting an oracle (e.g. me…

cs.LG2020

CLOPS: Continual Learning of Physiological Signals

Dani Kiyasseh, Tingting Zhu, David A. Clifton

Deep learning algorithms are known to experience destructive interference when instances violate the assumption of being independent and identically distributed (i.i.d). This viola…