Cían Hughes

Advancing conversational diagnostic AI with multimodal reasoning

Khaled Saab, Chunjong Park, Tim Strother, Jan Freyberg et autres

Real-world clinical practice is inherently multimodal, relying on the synthesis of patient history with visual information such as medical imagery and clinical documents. Although large language models (LLMs) have shown promise in diagnostic dialogue, their evaluation has been largely restricted to text-only …

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Does Duct-to-Duct Anastomosis Using an Eversion Technique Reduce Biliary Complications in Living Donor Liver Transplantation: A Prospective Analysis

Sabin Subedi, Godwin Packiaraj, Vikraman Gunabushanam, Cían Hughes et autres

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0819 Quantifying skin pigment: Comparison of five low-cost devices to the konica minolta CM-700d

B. R. ALFORD, Luis A. Ortiz, Ernesto Behnke, Dake Chen et autres

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Towards physician-centered oversight of conversational diagnostic AI

Elahe Vedadi, David Barrett, Natalie Harris, Ellery Wulczyn et autres

Recent work has demonstrated the promise of conversational AI systems for diagnostic dialogue. However, real-world assurance of patient safety means that providing individual diagnoses and treatment plans is considered a regulated activity by licensed professionals. Furthermore, physicians commonly oversee other team members …

MedGemma 1.5 Technical Report

Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri, Atilla P. Kiraly et autres

Artificial intelligence (AI) has significant potential in healthcare applications, but its training and deployment faces challenges due to healthcare's diverse data, complex tasks, and the need to preserve privacy. Foundation models that perform well on medical tasks and require less task-specific tuning …

Advancing Conversational Diagnostic AI with Multimodal Reasoning

Ryutaro Tanno, Khaled Saab, Jan Freyberg, Chunjong Park et autres

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Deep learning based linear energy transfer calculation for proton therapy

Xueyan Tang, H. Wan Chan Tseung, D Moseley, Alexei Zverovitch et autres

Abstract Objective. This study aims to address the limitations of traditional methods for calculating linear energy transfer (LET), a critical component in assessing relative biological effectiveness (RBE). Currently, Monte Carlo (MC) simulation, the gold-standard for accuracy, is resource-intensive and slow for dose …

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Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study

Mike Schaekermann, Terry Spitz, M.N. Pyles, Heather Cole-Lewis et autres

Background: Artificial intelligence (AI) has repeatedly been shown to encode historical inequities in healthcare. We aimed to develop a framework to quantitatively assess the performance equity of health AI technologies and to illustrate its utility via a case study. Methods: Here, we …

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Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning

J. John Lucido, T.A. DeWees, Todd R. Leavitt, Aman Anand et autres

Introduction: Organ-at-risk segmentation for head and neck cancer radiation therapy is a complex and time-consuming process (requiring up to 42 individual structure, and may delay start of treatment or even limit access to function-preserving care. Feasibility of using a deep learning (DL) …

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Study Design: Validation of clinical acceptability of deep-learning-based automated segmentation of organs-at-risk for head-and-neck radiotherapy treatment planning

Aman Anand, Chris Beltran, Mark D. Brooke, Justine R. Buroker et autres

Abstract This document reports the design of a retrospective study to validate the clinical acceptability of a deep-learning-based model for the autosegmentation of organs-at-risk (OARs) for use in radiotherapy treatment planning for head & neck (H&N) cancer patients.

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Predicting the immediate impact of national lockdown on neovascular age-related macular degeneration and associated visual morbidity: an INSIGHT Health Data Research Hub for Eye Health report

Susan P. Mollan, Dun Jack Fu, Ching‐Yi Chuo, Jacqueline G Gannon et autres

OBJECTIVE: Predicting the impact of neovascular age-related macular degeneration (nAMD) service disruption on visual outcomes following national lockdown in the UK to contain SARS-CoV-2. METHODS AND ANALYSIS: This retrospective cohort study includes deidentified data from 2229 UK patients from the INSIGHT Health …

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Clinically Applicable Segmentation of Head and Neck Anatomy for Radiotherapy: Deep Learning Algorithm Development and Validation Study

Stanislav Nikolov, Sam Blackwell, Alexei Zverovitch, R. Mendes et autres

BACKGROUND: Over half a million individuals are diagnosed with head and neck cancer each year globally. Radiotherapy is an important curative treatment for this disease, but it requires manual time to delineate radiosensitive organs at risk. This planning process can delay treatment …

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