6 papers
Position: Medical AI Neglects Real Treatment Outcomes
Shiva Kaul, Anjum Khurshid
Medical AI has rapidly improved its ability to perform diagnostic and prognostic tasks that lead to treatment decisions. But understanding of treatment itself is still inadequately…
The Verbose Context Problem in Medical Records
Shiva Kaul, Min-Gyu Kim, Anjum Khurshid +1
The verbose context problem occurs when structured concepts have token-inefficient textual representations. This bottleneck is acute in population health: cohort-level analysis of…
How Balanced Should Causal Covariates Be?
Shiva Kaul, Min-Gyu Kim
Covariate balancing is a popular technique for controlling confounding in observational studies. It finds weights for the treatment group which are close to uniform, but make the g…
Meta-Analysis with Untrusted Data
Shiva Kaul, Geoffrey J. Gordon
[See paper for full abstract] Meta-analysis is a crucial tool for answering scientific questions. It is usually conducted on a relatively small amount of ``trusted'' data -- ideall…
Embedding parameters in ab initio theory to develop approximations based on molecular similarity
Matteus Tanha, Haichen Li, Shiva Kaul +3
A means to take advantage of molecular similarity to lower the computational cost of electronic structure theory is explored, in which parameters are embedded into a low-cost, low-…
Embedding parameters in ab initio theory to develop well-controlled approximations based on molecular similarity
Matteus Tanha, Shiva Kaul, Alex Cappiello +2
A means to take advantage of molecular similarity to lower the computational cost of electronic structure theory is proposed, in which parameters are embedded into a low-cost, low-…