The Segment Anything Model (SAM) was fine-tuned on the EchoNet-Dynamic dataset and evaluated on external transthoracic echocardiography (TTE) and Point-of-Care Ultrasound (POCUS) datasets from CAMUS (University Hospital of St Etienne) and Mayo Clinic (99…
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In acute ischemic stroke due to large-vessel occlusion (AIS-LVO), late-window endovascular thrombectomy (EVT) decisions depend on penumbra-to-core (P:C) mismatch from computed tomographic perfusion (CTP). We developed multiple machine learning (ML) models to predict P:C…
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This paper proposes a “True Lifecycle Approach” (TLA) towards governing healthcare AI. The TLA governance model embeds core healthcare law principles—like informed consent, liability, and patient rights—throughout AI’s development, deployment, and use. Unlike narrow…
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Large language models (LLMs) are transforming the landscape of healthcare research, yet their role in qualitative analysis remains underexplored. This study compares human-led and LLM-assisted approaches to analyzing cancer patient narratives, using 33 semi-structured…
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Algorithmic bias occurs when predictive model performance varies meaningfully across sociodemographic classes, exacerbating systemic healthcare disparities. NYC Health + Hospitals, an urban safety net system, assessed bias in two binary classification models in our…
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To evaluate the effectiveness of a digital medication system in improving adherence among patients with serious mental disorders (SMD), we conducted a cluster-randomized controlled trial across 30 communities in Beijing. Participants, aged 18–65 years,…
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Neurological conditions, including dementia, pose a major public health challenge, contributing to a significant and growing clinical, economic, and societal burden. Traditionally, research and clinical practice have focused on diseases like dementia in isolation….
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Artificial intelligence (AI), particularly large language models (LLMs), is increasingly integrated into mental health care. This study examined racial bias in psychiatric diagnosis and treatment across four leading LLMs: Claude, ChatGPT, Gemini, and NewMes-15…
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Gambling harm is a global public health challenge. Gambling is often recorded in settings using routinely collected data (RCD). Linking of existing RCD affords numerous opportunities for policy-led research on gambling harm and early…
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Corneal opacification impairs vision and may necessitate surgery. Ipsilateral rotational autokeratoplasty (IRA) offers an alternative to allograft keratoplasty for treating localized opacities within the visual axis while minimizing risks. A novel digital twin software…
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