William Lotter

According to our database, William Lotter authored at least 19 papers between 2015 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2025

Beyond Diagnosis: Evaluating Multimodal LLMs for Pathology Localization in Chest Radiographs.

Advait Gosai, Arun Kavishwar, Stephanie L. McNamara, Soujanya Samineni, Renato Umeton, Alexander Chowdhury, William Lotter

CoRR, September, 2025

Comparing Computational Pathology Foundation Models using Representational Similarity Analysis.

Vaibhav Mishra, William Lotter

CoRR, September, 2025

Simulating Clinical AI Assistance using Multimodal LLMs: A Case Study in Diabetic Retinopathy.

Nadim Barakat, William Lotter

CoRR, September, 2025

AdvDINO: Domain-Adversarial Self-Supervised Representation Learning for Spatial Proteomics.

Stella Su, Marc Harary, Scott J. Rodig, William Lotter

CoRR, August, 2025

How AI is used in FDA-authorized medical devices: a taxonomy across 1,016 authorizations.

Rohan Singh, Monika Bapna, Abdul Rahman Diab, Emily S. Ruiz, William Lotter

npj Digit. Medicine, 2025

2024

The clinician-AI interface: intended use and explainability in FDA-cleared AI devices for medical image interpretation.

Stephanie L. McNamara, Paul H. Yi, William Lotter

npj Digit. Medicine, 2024

Fluoroformer: Scaling multiple instance learning to multiplexed images via attention-based channel fusion.

Marc Harary, Eliezer M. Van Allen, William Lotter

CoRR, 2024

Beyond Structured Attributes: Image-Based Predictive Trends for Chest X-Ray Classification.

Katharina V. Hoebel, Jesseba Fernando, William Lotter

Proceedings of the Medical Imaging with Deep Learning, 3-5 July 2024, Paris, France., 2024

2023

Representing visual classification as a linear combination of words.

Shobhit Agarwal, Yevgeniy R. Semenov, William Lotter

Proceedings of the Machine Learning for Health, 2023

2020

A neural network trained for prediction mimics diverse features of biological neurons and perception.

William Lotter, Gabriel Kreiman, David D. Cox

Nat. Mach. Intell., 2020

Synthesizing lesions using contextual GANs improves breast cancer classification on mammograms.

Eric Wu, Kevin Wu, William Lotter

CoRR, 2020

2019

Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach.

William Lotter, Abdul Rahman Diab, Bryan Haslam, Jiye G. Kim, Giorgia Grisot, Eric Wu, Kevin Wu, Jorge Onieva Onieva, Jerrold L. Boxerman, Meiyun Wang, Mack Bandler, Gopal Vijayaraghavan, A. Gregory Sorensen

CoRR, 2019

Validation of a deep learning mammography model in a population with low screening rates.

Kevin Wu, Eric Wu, Yaping Wu, Hongna Tan, Greg Sorensen, Meiyun Wang, Bill Lotter

CoRR, 2019

2018

A neural network trained to predict future video frames mimics critical properties of biological neuronal responses and perception.

William Lotter, Gabriel Kreiman, David D. Cox

CoRR, 2018

Conditional Infilling GANs for Data Augmentation in Mammogram Classification.

Eric Wu, Kevin Wu, David D. Cox, William Lotter

Proceedings of the Image Analysis for Moving Organ, Breast, and Thoracic Images, 2018

2017

Recurrent computations for visual pattern completion.

Hanlin Tang, Bill Lotter, Martin Schrimpf, Ana Paredes, Josue Ortega Caro, Walter Hardesty, David D. Cox, Gabriel Kreiman

CoRR, 2017

A Multi-scale CNN and Curriculum Learning Strategy for Mammogram Classification.

William Lotter, Greg Sorensen, David D. Cox

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning.

William Lotter, Gabriel Kreiman, David D. Cox

Proceedings of the 5th International Conference on Learning Representations, 2017

2015

Unsupervised Learning of Visual Structure using Predictive Generative Networks.

William Lotter, Gabriel Kreiman, David D. Cox

CoRR, 2015