Search Results for author: William Speier

Found 13 papers, 4 papers with code

High Performance P300 Spellers Using GPT2 Word Prediction With Cross-Subject Training

no code implementations22 May 2024 Nithin Parthasarathy, James Soetedjo, Saarang Panchavati, Nitya Parthasarathy, Corey Arnold, Nader Pouratian, William Speier

Amyotrophic lateral sclerosis (ALS) severely impairs patients' ability to communicate, often leading to a decline in their quality of life within a few years of diagnosis.

Brain Computer Interface EEG

Ultrasound Image Enhancement using CycleGAN and Perceptual Loss

1 code implementation18 Dec 2023 Shreeram Athreya, Ashwath Radhachandran, Vedrana Ivezić, Vivek Sant, Corey W. Arnold, William Speier

These images are compared with paired images acquired from high resolution devices to demonstrate the model's ability to generate realistic high-quality images across organ systems.

Generative Adversarial Network Image Enhancement +1

Predicting Thrombectomy Recanalization from CT Imaging Using Deep Learning Models

no code implementations8 Feb 2023 Haoyue Zhang, Jennifer S. Polson, Eric J. Yang, Kambiz Nael, William Speier, Corey W. Arnold

This is a promising result that supports future applications of deep learning on CT and CTA for the identification of eligible AIS patients for MTB.

Computed Tomography (CT) Decision Making

Design considerations for a hierarchical semantic compositional framework for medical natural language understanding

no code implementations5 Apr 2022 Ricky K. Taira, Anders O. Garlid, William Speier

Medical natural language processing (NLP) systems are a key enabling technology for transforming Big Data from clinical report repositories to information used to support disease models and validate intervention methods.

Natural Language Understanding Semantic Composition +1

Intra-Domain Task-Adaptive Transfer Learning to Determine Acute Ischemic Stroke Onset Time

no code implementations5 Nov 2020 Haoyue Zhang, Jennifer S Polson, Kambiz Nael, Noriko Salamon, Bryan Yoo, Suzie El-Saden, Fabien Scalzo, William Speier, Corey W Arnold

We apply this approach to both 2D and 3D CNN architectures with our top model achieving an ROC-AUC value of 0. 74, with a sensitivity of 0. 70 and a specificity of 0. 81 for classifying TSS < 4. 5 hours.

Specificity Transfer Learning

A Multi-resolution Model for Histopathology Image Classification and Localization with Multiple Instance Learning

no code implementations5 Nov 2020 Jiayun Li, Wenyuan Li, Anthony Sisk, Huihui Ye, W. Dean Wallace, William Speier, Corey W. Arnold

Large numbers of histopathological images have been digitized into high resolution whole slide images, opening opportunities in developing computational image analysis tools to reduce pathologists' workload and potentially improve inter- and intra- observer agreement.

General Classification Image Classification +2

Bidirectional Representation Learning from Transformers using Multimodal Electronic Health Record Data to Predict Depression

1 code implementation26 Sep 2020 Yiwen Meng, William Speier, Michael K. Ong, Corey W. Arnold

We applied the current trend of pretraining and fine-tuning on EHR data to outperform the current state-of-the-art in chronic disease prediction, and to demonstrate the underlying relation between EHR codes in the sequence.

Decision Making Disease Prediction +1

Attention-Guided Discriminative Region Localization and Label Distribution Learning for Bone Age Assessment

1 code implementation30 May 2020 Chao Chen, Zhihong Chen, Xinyu Jin, Lanjuan Li, William Speier, Corey W. Arnold

However, training with the global image underutilizes discriminative local information, while providing extra annotations is expensive and subjective.

Age Estimation regression

Translating neural signals to text using a Brain-Machine Interface

1 code implementation9 Jul 2019 Janaki Sheth, Ariel Tankus, Michelle Tran, Nader Pouratian, Itzhak Fried, William Speier

Brain-Computer Interfaces (BCI) help patients with faltering communication abilities due to neurodegenerative diseases produce text or speech output by direct neural processing.

An attention-based multi-resolution model for prostate whole slide imageclassification and localization

no code implementations30 May 2019 Jiayun Li, Wenyuan Li, Arkadiusz Gertych, Beatrice S. Knudsen, William Speier, Corey W. Arnold

The model achieved state-of-the-art performance for prostate cancer grading with an accuracy of 85. 11\% for classifying benign, low-grade (Gleason grade 3+3 or 3+4), and high-grade (Gleason grade 4+3 or higher) slides on an independent test set.

General Classification Multiple Instance Learning

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