This study aims to quantify the financial and environmental savings associated with remote follow up in patients undergoing lower limb arterial surgery. A prospective observational study evaluating financial cost(fC) and environmental cost(eC) of postoperative…
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Transgender and gender diverse (TGD) individuals face significant healthcare barriers, resulting in inequities and unmet needs. Mobile health (mHealth) applications offer promising solutions by providing accessible, cost-effective, personalized, and gender-affirming care. This systematic review,…
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Few studies have investigated quality of life (QoL) improvements in patients with colorectal cancer or the benefits of digital healthcare interventions. This randomized controlled trial assessed the impact of mobile applications on postoperative QoL…
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The assessment of voice quality plays a critical role in the clinical evaluation of hoarseness. However, no study has established a highly accurate method for the auditory–perceptual judgment of vocal roughness, which is one…
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Determining tumor microsatellite status has significant clinical value because tumors that are microsatellite instability-high (MSI-H) or mismatch repair deficient (dMMR) respond well to immune checkpoint inhibitors (ICIs) and oftentimes not to chemotherapeutics. We propose…
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We are an interdisciplinary team of researchers that are working to advance algorithmic fairness in the research of opioid use disorders. We discuss challenges that our research team faced when engaging with our Advisory…
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Deep learning techniques have significantly enhanced the convenience and precision of ultrasound image diagnosis, particularly in the crucial step of lesion segmentation. However, recent studies reveal that both train-from-scratch models and pre-trained models often…
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Sepsis is a dysregulated host response to infection with high mortality and morbidity. Early detection and intervention have been shown to improve patient outcomes, but existing computational models relying on structured electronic health record…
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Federated learning (FL) enables collaborative analysis of decentralized medical data while preserving patient privacy. However, the covariate shift from demographic and clinical differences can reduce model generalizability. We propose FedWeight, a novel FL framework…
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Detailed social determinants of health (SDoH) is often buried within clinical text in EHRs. Most current NLP efforts for SDoH have limitations, investigating limited factors, deriving data from a single institution, using specific patient…
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