Vision-language models (VLMs) show promise for answering clinically relevant questions, but their robustness to medical image artefacts remains unclear. We evaluated VLMs’ robustness through their performance on images with and without weak artefacts across…
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As an effective strategy for preventing influenza, vaccination uptake remains suboptimal. This cluster randomised trial evaluated digital messaging nudges on influenza vaccination among children aged 6-35 months and their parents in China. During 2024-25…
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Alzheimer’s Disease (AD), the most common neurodegenerative disease, is underdiagnosed and more prominent in underrepresented groups. We performed semi-supervised positive unlabeled learning (SSPUL) coupled with racial bias mitigation for equitable prediction of undiagnosed AD…
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Accurate detection of lung cancer from Computed Tomography (CT) scans is vital for improving patient survival but remains challenging for deep learning models, which struggle with scale variations of pulmonary nodules and the complex…
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Effective risk stratification is essential in clinical practice, enabling better resource allocation and improved patient outcomes. Although machine learning models have been widely used for risk prediction and stratification in electronic health record (EHR)…
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Lung cancer remains the top cause of cancer death, demanding consistent decisions. This clinically oriented review synthesizes computer-aided diagnosis across classical imaging, machine learning, and deep learning, emphasizing bedside-proven advances: multimodal CT/PET–clinical fusion; small-data…
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Artificial intelligence models analyzing speech show remarkable promise for identifying cognitive decline, achieving performance comparable to clinical assessments. However, their “black box” nature poses significant barriers to clinical adoption, as healthcare professionals require transparent…
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Wearable and health app data hold significant potential for healthcare and research, yet fragmented consent mechanisms create challenges for ethical, transparent, and user-controlled data sharing. We describe a centralised consent management system with a…
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The effectiveness of digital health management (DM) in post-discharge care for patients with coronary artery disease (CAD) remains insufficiently explored, particularly across public health emergencies. A total of 24,129 patients with CAD enrolled in…
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Rare diseases (RD) affect 3.5–5.9% of the global population, yet patients often endure a diagnostic odyssey averaging around 5–6 years, navigating multiple specialties and referrals. This study investigates the use of information content (IC)…
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