FUSING BRILLIANCE: EVALUATING THE ENCODER-DECODER HYBRIDS WITH CNN AND SWIN TRANSFORMER FOR MEDICAL SEGMENTATION

Fusing Brilliance: Evaluating the Encoder-Decoder Hybrids With CNN and Swin Transformer for Medical Segmentation

U-Net has become a standard model for medical image segmentation, alleviating the challenges posed by the costly acquisition and labeling TOOTHPASTE CITRUS SPICE BLEND of medical data.The convolutional layer, a fundamental component of U-Net, is renowned for its ability to incorporate inductive bias and efficiently extract local features.Building u

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Using Wearable Digital Devices to Screen Children for Mental Health Conditions: Ethical Promises and Challenges

In response to a burgeoning pediatric mental health epidemic, recent guidelines have instructed pediatricians to regularly screen their patients for mental health disorders with consistency and standardization.Yet, gold-standard screening surveys to evaluate mental health problems in children typically rely solely on reports given by caregivers, wh

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