146 citations · 288 across the 9 of their papers we have counts for
10 papers
Roadmap on Deep Learning for Microscopy
Giovanni Volpe, Carolina Wählby, Lei Tian +72
Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasin…
One-shot skill assessment in high-stakes domains with limited data via meta learning
Erim Yanik, Steven Schwaitzberg, Gene Yang +4
Deep Learning (DL) has achieved robust competency assessment in various high-stakes fields. However, the applicability of DL models is often hampered by their substantial data requ…
Video-based Formative and Summative Assessment of Surgical Tasks using Deep Learning
Erim Yanik, Uwe Kruger, Xavier Intes +2
To ensure satisfactory clinical outcomes, surgical skill assessment must be objective, time-efficient, and preferentially automated - none of which is currently achievable. Video-b…
Deep Learning in fNIRS: A review
Condell Eastmond, Aseem Subedi, Suvranu De +1
Significance: Optical neuroimaging has become a well-established clinical and research tool to monitor cortical activations in the human brain. It is notable that outcomes of funct…
Deep learning in biomedical optics
Lei Tian, Brady Hunt, Muyinatu A. Lediju Bell +5
This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical opt…
Deep Neural Networks for the Assessment of Surgical Skills: A Systematic Review
Erim Yanik, Xavier Intes, Uwe Kruger +6
Surgical training in medical school residency programs has followed the apprenticeship model. The learning and assessment process is inherently subjective and time-consuming. Thus,…