Quantum-SpinalNet: a hybrid deep learning approach for mammographic breast cancer detection

IntroductionBreast cancer diagnosis in mammograms remains challenging due to limitations in preprocessing, accurate differentiation of benign and malignant cases, and precise tumor segmentation.MethodsWe propose Quantum-SpinalNet, a hybrid deep learning model combining Swin ResUNet3+ for tumor segmentation with a Deep Quantum Neural Network (DQNN) and SpinalNet for classification. Preprocessing involves CEAMF-based denoising, Z-score normalization, and context-aware […]

Blurring the lines of healthcare AI

If you asked me a year ago to break down the different areas of healthcare AI we’re covering, it might’ve looked like scribes, clinical decision support and a whole lot of administrative use cases, like …

Measuring and reducing surgical staff stress in a realistic operating room setting using EDA monitoring and smart hearing protection

BackgroundStress is a critical factor in the operating room (OR) and affects both the performance and well-being of surgical staff. Measuring and mitigating this stress can therefore improve patient safety and healthcare worker health.ObjectiveThis study aimed to evaluate the stress levels of OR staff in a simulated surgical setting using electrodermal activity (EDA) and to […]

Bioethical considerations in deploying mobile mental health apps in LMIC settings: insights from the MITHRA pilot study in rural India

IntroductionIn India, untreated depression among women contributes significantly to morbidity and mortality, underscoring an urgent need for accessible and ethically grounded mental health interventions. Mobile health (mHealth) tools offer scalable solutions; however, their implementation in low- and middle-income country (LMIC) settings raises important bioethical considerations.MethodsThis study was conducted at the conclusion of a pilot randomized […]

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