3 citations · 12 across the 11 of their papers we have counts for
13 papers
Unlocking the Power of Medical Tabular Data via Semantic-Aware Multimodal Pre-training
Yingsheng Liu, Haiming Li, Jingmin Zhu +6
While vision-language models dominate medical representation learning, unstructured text lacks the dense, quantitative diagnostic phenotypes inherent in structured clinical tables.…
A Vision-Language Foundation Model for Zero-shot Clinical Collaboration and Automated Concept Discovery in Dermatology
Siyuan Yan, Xieji Li, Dan Mo +28
Medical foundation models have shown promise in controlled benchmarks, yet widespread deployment remains hindered by reliance on task-specific fine-tuning. Here, we introduce DermF…
Multi-Aspect Knowledge-Enhanced Medical Vision-Language Pretraining with Multi-Agent Data Generation
Xieji Li, Siyuan Yan, Yingsheng Liu +4
Vision-language pretraining (VLP) has emerged as a powerful paradigm in medical image analysis, enabling representation learning from large-scale image-text pairs without relying o…
Supporting Data-Frame Dynamics in AI-assisted Decision Making
Chengbo Zheng, Tim Miller, Alina Bialkowski +2
High stakes decision-making often requires a continuous interplay between evolving evidence and shifting hypotheses, a dynamic that is not well supported by current AI decision sup…
The iToBoS dataset: skin region images extracted from 3D total body photographs for lesion detection
Anup Saha, Joseph Adeola, Nuria Ferrera +14
Artificial intelligence has significantly advanced skin cancer diagnosis by enabling rapid and accurate detection of malignant lesions. In this domain, most publicly available imag…
A Multimodal Vision Foundation Model for Clinical Dermatology
Siyuan Yan, Zhen Yu, Clare Primiero +22
Diagnosing and treating skin diseases require advanced visual skills across domains and the ability to synthesize information from multiple imaging modalities. While current deep l…
From Evidence to Decision: Exploring Evaluative AI
Thao Le, Tim Miller, Liz Sonenberg +2
This paper presents a hypothesis-driven approach to improve AI-supported decision-making that is based on the Evaluative AI paradigm - a conceptual framework that proposes providin…
Prompt-driven Latent Domain Generalization for Medical Image Classification
Siyuan Yan, Chi Liu, Zhen Yu +7
Deep learning models for medical image analysis easily suffer from distribution shifts caused by dataset artifacts bias, camera variations, differences in the imaging station, etc.…
Revamping AI Models in Dermatology: Overcoming Critical Challenges for Enhanced Skin Lesion Diagnosis
Deval Mehta, Brigid Betz-Stablein, Toan D Nguyen +8
The surge in developing deep learning models for diagnosing skin lesions through image analysis is notable, yet their clinical black faces challenges. Current dermatology AI models…
Ugly Ducklings or Swans: A Tiered Quadruplet Network with Patient-Specific Mining for Improved Skin Lesion Classification
Nathasha Naranpanawa, H. Peter Soyer, Adam Mothershaw +4
An ugly duckling is an obviously different skin lesion from surrounding lesions of an individual, and the ugly duckling sign is a criterion used to aid in the diagnosis of cutaneou…
Application of Machine Learning in Melanoma Detection and the Identification of 'Ugly Duckling' and Suspicious Naevi: A Review
Fatima Al Zegair, Nathasha Naranpanawa, Brigid Betz-Stablein +3
Skin lesions known as naevi exhibit diverse characteristics such as size, shape, and colouration. The concept of an "Ugly Duckling Naevus" comes into play when monitoring for melan…
EPVT: Environment-aware Prompt Vision Transformer for Domain Generalization in Skin Lesion Recognition
Siyuan Yan, Chi Liu, Zhen Yu +6
Skin lesion recognition using deep learning has made remarkable progress, and there is an increasing need for deploying these systems in real-world scenarios. However, recent resea…
A Patient-Centric Dataset of Images and Metadata for Identifying Melanomas Using Clinical Context
Veronica Rotemberg, Nicholas Kurtansky, Brigid Betz-Stablein +21
Prior skin image datasets have not addressed patient-level information obtained from multiple skin lesions from the same patient. Though artificial intelligence classification algo…