Daniel Shu Wei Ting
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View article: Augmented intelligence: An emerging paradigm for AI in healthcare
Augmented intelligence: An emerging paradigm for AI in healthcare Open
Artificial intelligence (AI) is rapidly transforming healthcare, providing tools that support diagnosis, streamline workflows and enhance patient outcomes. However, its adoption has been uneven—hindered by ethical, legal and operational co…
View article: Gender Bias in Large Language Models for Healthcare: Assignment Consistency and Clinical Implications
Gender Bias in Large Language Models for Healthcare: Assignment Consistency and Clinical Implications Open
The integration of large language models (LLMs) into healthcare holds promise to enhance clinical decision-making, yet their susceptibility to biases remains a critical concern. Gender has long influenced physician behaviors and patient ou…
View article: How can artificial intelligence transform the training of medical students and physicians?
How can artificial intelligence transform the training of medical students and physicians? Open
Advances in artificial intelligence (AI), particularly generative AI, hold promise for transforming medical education and physician training in response to increasing health-care demands and shortages in the global health-care workforce. M…
View article: EVLF-FM: Explainable Vision Language Foundation Model for Medicine
EVLF-FM: Explainable Vision Language Foundation Model for Medicine Open
Despite the promise of foundation models in medical AI, current systems remain limited - they are modality-specific and lack transparent reasoning processes, hindering clinical adoption. To address this gap, we present EVLF-FM, a multimoda…
View article: Large language model as clinical decision support system augments medication safety in 16 clinical specialties
Large language model as clinical decision support system augments medication safety in 16 clinical specialties Open
Large language models (LLMs) have emerged as tools to support healthcare delivery, from automating tasks to aiding clinical decision-making. This study evaluated LLMs as alternative to rule-based alert systems, focusing on their ability to…
View article: Development and evaluation of a lightweight large language model chatbot for medication enquiry
Development and evaluation of a lightweight large language model chatbot for medication enquiry Open
Large Language Models (LLMs) show promise in augmenting digital health applications. However, development and scaling of large models face computational constraints, data security concerns and limitations of internet accessibility in some …
View article: Internal Limiting Membrane Flap Enhances Macular Hole Closure Rates in Highly Myopic Eyes: A Case-Control Study
Internal Limiting Membrane Flap Enhances Macular Hole Closure Rates in Highly Myopic Eyes: A Case-Control Study Open
Anatomical success was comparable between HM and non-HM eyes. Higher surgical success was associated with smaller MH size and ILM flap, but not influenced by AL, macular curvature or foveoschisis.
View article: A noninvasive model for chronic kidney disease screening and common pathological type identification from retinal images
A noninvasive model for chronic kidney disease screening and common pathological type identification from retinal images Open
Chronic kidney disease (CKD) is a global health challenge, but invasive renal biopsies, the gold standard for diagnosis and prognosis, are often clinically constrained. To address this, we developed the kidney intelligent diagnosis system …
View article: Clinical and economic impact of a large language model in perioperative medicine: a randomized crossover trial
Clinical and economic impact of a large language model in perioperative medicine: a randomized crossover trial Open
Preoperative assessment is a critical but time-consuming component of perioperative care, often hindered by poor guideline adherence and high documentation burdens. This study evaluates the impact of PEACH (PErioperative AI CHatbot), an LL…
View article: Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM)
Multimodal, Multi-Disease Medical Imaging Foundation Model (MerMED-FM) Open
Current artificial intelligence models for medical imaging are predominantly single modality and single disease. Attempts to create multimodal and multi-disease models have resulted in inconsistent clinical accuracy. Furthermore, training …
View article: The Evolving Landscape of Generative Large Language Models and Traditional Natural Language Processing in Medicine
The Evolving Landscape of Generative Large Language Models and Traditional Natural Language Processing in Medicine Open
Natural language processing (NLP) has been traditionally applied to medicine, and generative large language models (LLMs) have become prominent recently. However, the differences between them across different medical tasks remain underexpl…
View article: Large Language Models in Randomized Controlled Trials Design: Observational Study
Large Language Models in Randomized Controlled Trials Design: Observational Study Open
Background Randomized controlled trials (RCTs) face challenges such as limited generalizability, insufficient recruitment diversity, and high failure rates, often due to restrictive eligibility criteria and inefficient patient selection. L…
View article: Retrieval augmented generation for 10 large language models and its generalizability in assessing medical fitness
Retrieval augmented generation for 10 large language models and its generalizability in assessing medical fitness Open
Large Language Models (LLMs) hold promise for medical applications but often lack domain-specific expertise. Retrieval Augmented Generation (RAG) enables customization by integrating specialized knowledge. This study assessed the accuracy,…
View article: Artificial intelligence‐quantified schisis volume as a structural endpoint for gene therapy clinical trials in X‐linked retinoschisis
Artificial intelligence‐quantified schisis volume as a structural endpoint for gene therapy clinical trials in X‐linked retinoschisis Open
Purpose To use artificial intelligence (AI) for quantifying schisis volume (ASV) in X‐linked retinoschisis (XLRS) for use as a structural endpoint in gene therapy clinical trials. Methods We used data from Singapore, the United Kingdom, th…
View article: PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods
PROBAST+AI: an updated quality, risk of bias, and applicability assessment tool for prediction models using regression or artificial intelligence methods Open
The Prediction model Risk Of Bias ASsessment Tool (PROBAST) is used to assess the quality, risk of bias, and applicability of prediction models or algorithms and of prediction model/algorithm studies. Since PROBAST’s introduction in 2019, …
View article: Retrieval-augmented generation for generative artificial intelligence in health care
Retrieval-augmented generation for generative artificial intelligence in health care Open
Generative artificial intelligence has brought disruptive innovations in health care but faces certain challenges. Retrieval-augmented generation (RAG) enables models to generate more reliable content by leveraging the retrieval of externa…
View article: Oculomics meets exposomics: a roadmap for applying multi-modal ocular biomarkers in precision environmental health research
Oculomics meets exposomics: a roadmap for applying multi-modal ocular biomarkers in precision environmental health research Open
Precision environmental health (PEH) is an emerging field that seeks to understand how diverse environmental exposures interact with individual biological and genetic factors to influence health outcomes. While recent advances in exposomic…
View article: Real-world Deployment and Evaluation of PErioperative AI CHatbot (PEACH) -- a Large Language Model Chatbot for Perioperative Medicine
Real-world Deployment and Evaluation of PErioperative AI CHatbot (PEACH) -- a Large Language Model Chatbot for Perioperative Medicine Open
Large Language Models (LLMs) are emerging as powerful tools in healthcare, particularly for complex, domain-specific tasks. This study describes the development and evaluation of the PErioperative AI CHatbot (PEACH), a secure LLM-based sys…
View article: Retrieval Augmented Generation for 10 Large Language Models and its Generalizability in Assessing Medical Fitness
Retrieval Augmented Generation for 10 Large Language Models and its Generalizability in Assessing Medical Fitness Open
Purpose: Large Language Models (LLMs) offer potential for medical applications, but often lack the specialized knowledge needed for clinical tasks. Retrieval Augmented Generation (RAG) is a promising approach, allowing for the customizatio…
View article: Mitigating Cognitive Biases in Clinical Decision-Making Through Multi-Agent Conversations Using Large Language Models: Simulation Study
Mitigating Cognitive Biases in Clinical Decision-Making Through Multi-Agent Conversations Using Large Language Models: Simulation Study Open
Background Cognitive biases in clinical decision-making significantly contribute to errors in diagnosis and suboptimal patient outcomes. Addressing these biases presents a formidable challenge in the medical field. Objective This study aim…
View article: Diagnostic performance of deep learning for infectious keratitis: a systematic review and meta-analysis
Diagnostic performance of deep learning for infectious keratitis: a systematic review and meta-analysis Open
NIH, Wellcome Trust, MRC, Fight for Sight, BHP, and ESCRS.