Browse by research highlights:

Precision Cancer Care

Histology Image Analysis

Real-World Healthcare Application

Foundational AI Research

Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder

Naofumi Tomita 6/13/23 Naofumi Tomita 6/13/23

Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder

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MHAttnSurv: Multi-head attention for survival prediction using whole-slide pathology images

BMIRDS . 4/5/23 BMIRDS . 4/5/23

MHAttnSurv: Multi-head attention for survival prediction using whole-slide pathology images

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Detection of Colorectal Adenocarcinoma and Grading Dysplasia on Histopathologic Slides Using Deep Learning

BMIRDS . 2/23/23 BMIRDS . 2/23/23

Detection of Colorectal Adenocarcinoma and Grading Dysplasia on Histopathologic Slides Using Deep Learning

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Graph Convolutional Neural Networks for Histologic Classification of Pancreatic Cancer

BMIRDS . 1/20/23 BMIRDS . 1/20/23

Graph Convolutional Neural Networks for Histologic Classification of Pancreatic Cancer

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Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder

BMIRDS . 1/10/23 BMIRDS . 1/10/23

Patient Engagement in a Multimodal Digital Phenotyping Study of Opioid Use Disorder

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AI-RADS: Successes and Challenges of a Novel Artificial Intelligence Curriculum for Radiologists across Different Delivery Formats

BMIRDS . 1/1/23 BMIRDS . 1/1/23

AI-RADS: Successes and Challenges of a Novel Artificial Intelligence Curriculum for Radiologists across Different Delivery Formats

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Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning

BMIRDS . 11/29/22 BMIRDS . 11/29/22

Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning

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Bladder Cancer Prognosis Using Deep Neural Networks and Histopathology Images

BMIRDS . 8/28/22 BMIRDS . 8/28/22

Bladder Cancer Prognosis Using Deep Neural Networks and Histopathology Images

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BMIRDS . 8/8/22 BMIRDS . 8/8/22

Quantifying Epithelial-Mesenchymal Heterogeneity and EMT Scoring in Tumor Samples via Tyramide Signal Amplification (TSA)

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Phenotypic Heterogeneity Driven by Plasticity of the Intermediate EMT State Governs Disease Progression and Metastasis in Breast Cancer

Naofumi Tomita 8/3/22 Naofumi Tomita 8/3/22

Phenotypic Heterogeneity Driven by Plasticity of the Intermediate EMT State Governs Disease Progression and Metastasis in Breast Cancer

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Predicting Oncogene Mutations of Lung Cancer Using Deep Learning and Histopathologic Features on Whole-Slide Images

Naofumi Tomita 7/28/22 Naofumi Tomita 7/28/22

Predicting Oncogene Mutations of Lung Cancer Using Deep Learning and Histopathologic Features on Whole-Slide Images

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Naofumi Tomita 7/9/22 Naofumi Tomita 7/9/22

Calibrating Histopathology Image Classifiers using Label Smoothing

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Naofumi Tomita 6/30/22 Naofumi Tomita 6/30/22

Enhancing Research Data Infrastructure to Address the Opioid Epidemic: The Opioid Overdose Network (02-Net)

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Naofumi Tomita 6/2/22 Naofumi Tomita 6/2/22

Estimating Clear Cell Renal Cell Carcinoma Transcriptomic Signatures Using Machine Learning and Histopathology Images

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Naofumi Tomita 4/29/22 Naofumi Tomita 4/29/22

The Feasibility and Utility of Harnessing Digital Health to Understand Clinical Trajectories in Medication Treatment for Opioid Use Disorder: D-TECT Study Design and Methodological Considerations

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Naofumi Tomita 4/28/22 Naofumi Tomita 4/28/22

Association Between Fat-Infiltrated Axillary Lymph Nodes on Screening Mammography and Cardiometabolic Disease

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Naofumi Tomita 2/15/22 Naofumi Tomita 2/15/22

Quantifying Epithelial-Mesenchymal Tumor Heterogeneity for Prediction of Patient Prognosis Based on EMT State

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BMIRDS . 11/18/21 BMIRDS . 11/18/21

Evaluation of an Artificial Intelligence–Augmented Digital System for Histologic Classification of Colorectal Polyps

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Naofumi Tomita 11/15/21 Naofumi Tomita 11/15/21

AI-RADS: An Artificial Intelligence Curriculum for Residents

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Naofumi Tomita 10/22/21 Naofumi Tomita 10/22/21

An Audio Personal Health Library of Clinic Visit Recordings for Patients and Their Caregivers (HealthPAL): User-Centered Design Approach

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