Renee Wong
A5060982337- Topic Modeling
- Machine Learning in Healthcare
- AI in cancer detection
- Artificial Intelligence in Healthcare and Education
- Cutaneous Melanoma Detection and Management
- Data-Driven Disease Surveillance
- Digital Mental Health Interventions
- Social Media in Health Education
- Natural Language Processing Techniques
- Digital Imaging in Medicine
- Biomedical Text Mining and Ontologies
- Mathematical Biology Tumor Growth
- Simulation Techniques and Applications
- Patient-Provider Communication in Healthcare
- Digital Imaging for Blood Diseases
- Empathy and Medical Education
- Body Image and Dysmorphia Studies
Google (United States)
2024-2025
Recent artificial intelligence (AI) systems have reached milestones in "grand challenges" ranging from Go to protein-folding. The capability retrieve medical knowledge, reason over it, and answer questions comparably physicians has long been viewed as one such grand challenge. Large language models (LLMs) catalyzed significant progress question answering; Med-PaLM was the first model exceed a "passing" score US Medical Licensing Examination (USMLE) style with of 67.2% on MedQA dataset....
BackgroundMedicine is inherently multimodal, requiring the simultaneous interpretation and integration of insights between many data modalities spanning text, imaging, genomics, more. Generalist biomedical artificial intelligence systems that flexibly encode, integrate, interpret these might better enable impactful applications ranging from scientific discovery to care delivery.MethodsTo catalyze development models, we curated MultiMedBench, a new multimodal benchmark. MultiMedBench...
Excellence in a wide variety of medical applications poses considerable challenges for AI, requiring advanced reasoning, access to up-to-date knowledge and understanding complex multimodal data. Gemini models, with strong general capabilities long-context offer exciting possibilities medicine. Building on these core strengths Gemini, we introduce Med-Gemini, family highly capable models that are specialized medicine the ability seamlessly use web search, can be efficiently tailored novel...
Large language models (LLMs) have shown promise in medical question answering, with Med-PaLM being the first to exceed a 'passing' score United States Medical Licensing Examination style questions. However, challenges remain long-form answering and handling real-world workflows. Here, we present 2, which bridges these gaps combination of base LLM improvements, domain fine-tuning new strategies for improving reasoning grounding through ensemble refinement chain retrieval. 2 scores up 86.5% on...
Medicine is inherently multimodal, with rich data modalities spanning text, imaging, genomics, and more. Generalist biomedical artificial intelligence (AI) systems that flexibly encode, integrate, interpret this at scale can potentially enable impactful applications ranging from scientific discovery to care delivery. To the development of these models, we first curate MultiMedBench, a new multimodal benchmark. MultiMedBench encompasses 14 diverse tasks such as medical question answering,...
Although skin concerns are common, access to specialist care is limited. Artificial intelligence (AI)-assisted tools support medical decisions may provide patients with feedback on their while also helping ensure the most urgent cases routed dermatologists. AI-based conversational agents have been explored recently, how they perceived by and clinicians not well understood. We conducted a Wizard-of-Oz study involving 18 participants real concerns. Participants were randomly assigned interact...
Importance Health datasets from clinical sources do not reflect the breadth and diversity of disease, impacting research, medical education, artificial intelligence tool development. Assessments novel crowdsourcing methods to create health are needed. Objective To evaluate if web search advertisements (ads) effective at creating a diverse representative dermatology image dataset. Design, Setting, Participants This prospective observational survey study, conducted March November 2023, used...
During the diagnostic process, doctors incorporate multimodal information including imaging and medical history - similarly AI development has increasingly become multimodal. In this paper we tackle a more subtle challenge: take targeted to obtain only most pertinent pieces of information; how do enable same? We develop wrapper method named MINT (Make your model INTeractive) that automatically determines what are valuable at each step, ask for useful information. demonstrate efficacy...
Background: Health datasets from clinical sources do not reflect the breadth and diversity of disease in real world, impacting research, medical education, artificial intelligence (AI) tool development. Dermatology is a suitable area to develop test new scalable method create representative health datasets. Methods: We used Google Search advertisements invite contributions an open access dataset images dermatology conditions, demographic symptom information. With informed contributor...