Search Results for author: Neil Tenenholtz

Found 8 papers, 2 papers with code

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains

1 code implementation6 Feb 2024 Junhong Shen, Neil Tenenholtz, James Brian Hall, David Alvarez-Melis, Nicolo Fusi

Large Language Models (LLMs) have demonstrated remarkable proficiency in understanding and generating natural language.

TAG Zero-shot Generalization

Improving mitosis detection on histopathology images using large vision-language models

no code implementations11 Oct 2023 Ruiwen Ding, James Hall, Neil Tenenholtz, Kristen Severson

In certain types of cancerous tissue, mitotic count has been shown to be associated with tumor proliferation, poor prognosis, and therapeutic resistance.

Domain Generalization Image Captioning +4

Best Practices and Scoring System on Reviewing A.I. based Medical Imaging Papers: Part 1 Classification

no code implementations3 Feb 2022 Timothy L. Kline, Felipe Kitamura, Ian Pan, Amine M. Korchi, Neil Tenenholtz, Linda Moy, Judy Wawira Gichoya, Igor Santos, Steven Blumer, Misha Ysabel Hwang, Kim-Ann Git, Abishek Shroff, Elad Walach, George Shih, Steve Langer

The goal of this series is to provide resources to not only help improve the review process for A. I.-based medical imaging papers, but to facilitate a standard for the information that is presented within all components of the research study.

Image Classification

Initialization and Regularization of Factorized Neural Layers

1 code implementation ICLR 2021 Mikhail Khodak, Neil Tenenholtz, Lester Mackey, Nicolò Fusi

In model compression, we show that they enable low-rank methods to significantly outperform both unstructured sparsity and tensor methods on the task of training low-memory residual networks; analogs of the schemes also improve the performance of tensor decomposition techniques.

Knowledge Distillation Model Compression +2

4D CNN for semantic segmentation of cardiac volumetric sequences

no code implementations17 Jun 2019 Andriy Myronenko, Dong Yang, Varun Buch, Daguang Xu, Alvin Ihsani, Sean Doyle, Mark Michalski, Neil Tenenholtz, Holger Roth

We propose a 4D convolutional neural network (CNN) for the segmentation of retrospective ECG-gated cardiac CT, a series of single-channel volumetric data over time.

Segmentation Semantic Segmentation

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