Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging

no code implementations • 26 Sep 2024 • Paul Weiser, Georg Langs, Wolfgang Bogner, Stanislav Motyka, Bernhard Strasser, Polina Golland, Nalini Singh, Jorg Dietrich, Erik Uhlmann, Tracy Batchelor, Daniel Cahill, Malte Hoffmann, Antoine Klauser, Ovidiu C. Andronesi

Methods: Fast high-resolution whole-brain metabolic imaging was performed at 3. 4 mm$^3$ isotropic resolution with acquisition times between 4:11-9:21 min:s using ECCENTRIC pulse sequence on a 7T MRI scanner.

Every Answer Matters: Evaluating Commonsense with Probabilistic Measures

1 code implementation • 6 Jun 2024 • Qi Cheng, Michael Boratko, Pranay Kumar Yelugam, Tim O'Gorman, Nalini Singh, Andrew McCallum, Xiang Lorraine Li

We also propose a method of probabilistic evaluation that strongly correlates with human judgments.

Common Sense Reasoning Language Modelling +1

UncertaINR: Uncertainty Quantification of End-to-End Implicit Neural Representations for Computed Tomography

1 code implementation • 22 Feb 2022 • Francisca Vasconcelos, Bobby He, Nalini Singh, Yee Whye Teh

To that end, we study a Bayesian reformulation of INRs, UncertaINR, in the context of computed tomography, and evaluate several Bayesian deep learning implementations in terms of accuracy and calibration.

Computed Tomography (CT) Decision Making +2

A deep learning system for differential diagnosis of skin diseases

no code implementations • 11 Sep 2019 • Yuan Liu, Ayush Jain, Clara Eng, David H. Way, Kang Lee, Peggy Bui, Kimberly Kanada, Guilherme de Oliveira Marinho, Jessica Gallegos, Sara Gabriele, Vishakha Gupta, Nalini Singh, Vivek Natarajan, Rainer Hofmann-Wellenhof, Greg S. Corrado, Lily H. Peng, Dale R. Webster, Dennis Ai, Susan Huang, Yun Liu, R. Carter Dunn, David Coz

In this paper, we developed a deep learning system (DLS) to provide a differential diagnosis of skin conditions for clinical cases (skin photographs and associated medical histories).

Deep Learning