Search Results for author: Vivek Natarajan

Found 24 papers, 5 papers with code

Towards Accurate Differential Diagnosis with Large Language Models

no code implementations30 Nov 2023 Daniel McDuff, Mike Schaekermann, Tao Tu, Anil Palepu, Amy Wang, Jake Garrison, Karan Singhal, Yash Sharma, Shekoofeh Azizi, Kavita Kulkarni, Le Hou, Yong Cheng, Yun Liu, S Sara Mahdavi, Sushant Prakash, Anupam Pathak, Christopher Semturs, Shwetak Patel, Dale R Webster, Ewa Dominowska, Juraj Gottweis, Joelle Barral, Katherine Chou, Greg S Corrado, Yossi Matias, Jake Sunshine, Alan Karthikesalingam, Vivek Natarajan

Comparing the two assisted study arms, the DDx quality score was higher for clinicians assisted by our LLM (top-10 accuracy 51. 7%) compared to clinicians without its assistance (36. 1%) (McNemar's Test: 45. 7, p < 0. 01) and clinicians with search (44. 4%) (4. 75, p = 0. 03).

Model reference adaptive control for state and input constrained linear systems

no code implementations23 Aug 2023 Sudipta Chattopadhyay, Srikant Sukumar, Vivek Natarajan

Several modifications of the model reference adaptive control (MRAC) framework have been proposed to address input constraints in uncertain linear systems.

The Capability of Large Language Models to Measure Psychiatric Functioning

no code implementations3 Aug 2023 Isaac R. Galatzer-Levy, Daniel McDuff, Vivek Natarajan, Alan Karthikesalingam, Matteo Malgaroli

The current work investigates the capability of Large language models (LLMs) that are explicitly trained on large corpuses of medical knowledge (Med-PaLM 2) to predict psychiatric functioning from patient interviews and clinical descriptions without being trained to do so.

Motion planning for parabolic equations using flatness and finite-difference approximations

no code implementations21 May 2023 Soham Chatterjee, Vivek Natarajan

We consider the problem of finding an input signal which transfers a linear boundary controlled 1D parabolic partial differential equation, with spatially-varying coefficients and a non-local term, from a given initial state to a desired final state.

Motion Planning

Adaptive identification of SISO linear infinite-dimensional systems

no code implementations19 May 2023 Sudipta Chattopadhyay, Srikant Sukumar, Vivek Natarajan

The unknown parameter can be reconstructed using the transfer function coefficient estimates obtained with n large and the algebraic expressions relating the transfer function coefficients to the unknown parameter.

Big Self-Supervised Models Advance Medical Image Classification

1 code implementation ICCV 2021 Shekoofeh Azizi, Basil Mustafa, Fiona Ryan, Zachary Beaver, Jan Freyberg, Jonathan Deaton, Aaron Loh, Alan Karthikesalingam, Simon Kornblith, Ting Chen, Vivek Natarajan, Mohammad Norouzi

Self-supervised pretraining followed by supervised fine-tuning has seen success in image recognition, especially when labeled examples are scarce, but has received limited attention in medical image analysis.

Contrastive Learning General Classification +3

Addressing the Real-world Class Imbalance Problem in Dermatology

no code implementations9 Oct 2020 Wei-Hung Weng, Jonathan Deaton, Vivek Natarajan, Gamaleldin F. Elsayed, YuAn Liu

Class imbalance is a common problem in medical diagnosis, causing a standard classifier to be biased towards the common classes and perform poorly on the rare classes.

Benchmarking Few-Shot Learning +1

DermGAN: Synthetic Generation of Clinical Skin Images with Pathology

no code implementations20 Nov 2019 Amirata Ghorbani, Vivek Natarajan, David Coz, Yu-An Liu

Despite the recent success in applying supervised deep learning to medical imaging tasks, the problem of obtaining large and diverse expert-annotated datasets required for the development of high performant models remains particularly challenging.

Data Augmentation

A deep learning system for differential diagnosis of skin diseases

no code implementations11 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).

Pythia v0.1: the Winning Entry to the VQA Challenge 2018

9 code implementations26 Jul 2018 Yu Jiang, Vivek Natarajan, Xinlei Chen, Marcus Rohrbach, Dhruv Batra, Devi Parikh

We demonstrate that by making subtle but important changes to the model architecture and the learning rate schedule, fine-tuning image features, and adding data augmentation, we can significantly improve the performance of the up-down model on VQA v2. 0 dataset -- from 65. 67% to 70. 22%.

Data Augmentation Visual Question Answering (VQA)

Cannot find the paper you are looking for? You can Submit a new open access paper.