718 citations
- Harvard UniversityUS102 papers
- Massachusetts Institute of TechnologyUS20 papers
- Massachusetts General HospitalUS17 papers
- University College LondonGB10 papers
- Brigham and Women's HospitalUS9 papers
- Athinoula A. Martinos Center for Biomedical ImagingUS8 papers
- Boston Children's MuseumUS8 papers
- Northeastern UniversityUS7 papers
- Centre National de la Recherche ScientifiqueFR6 papers
- Loyola University ChicagoUS6 papers
- University of LausanneCH6 papers
- University of PennsylvaniaUS6 papers
10 papers · 1 filter
Towards symbolic regression for interpretable clinical decision scores
Guilherme Seidyo Imai Aldeia, Joseph D. Romano, Fabricio Olivetti de Franca +2
Medical decision-making makes frequent use of algorithms that combine risk equations with rules, providing clear and standardized treatment pathways. Symbolic regression (SR) tradi…
Call for Action: towards the next generation of symbolic regression benchmark
Guilherme S. Imai Aldeia, Hengzhe Zhang, Geoffrey Bomarito +5
Symbolic Regression (SR) is a powerful technique for discovering interpretable mathematical expressions. However, benchmarking SR methods remains challenging due to the diversity o…
Revealing Vision-Language Integration in the Brain with Multimodal Networks
Vighnesh Subramaniam, Colin Conwell, Christopher Wang +4
We use (multi)modal deep neural networks (DNNs) to probe for sites of multimodal integration in the human brain by predicting stereoencephalography (SEEG) recordings taken while hu…
Learning the Regularization in DCE-MR Image Reconstruction for Functional Imaging of Kidneys
Aziz Koçanaoğulları, Cemre Ariyurek, Onur Afacan +1
Kidney DCE-MRI aims at both qualitative assessment of kidney anatomy and quantitative assessment of kidney function by estimating the tracer kinetic (TK) model parameters. Accurate…
Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review
Yuqi Si, Jingcheng Du, Zhao Li +5
Patient representation learning refers to learning a dense mathematical representation of a patient that encodes meaningful information from Electronic Health Records (EHRs). This…
Frivolous Units: Wider Networks Are Not Really That Wide
Stephen Casper, Xavier Boix, Vanessa D'Amario +4
A remarkable characteristic of overparameterized deep neural networks (DNNs) is that their accuracy does not degrade when the network's width is increased. Recent evidence suggests…