AI Medical Compendium

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Partial-Label Contrastive Representation Learning for Fine-Grained Biomarkers Prediction From Histopathology Whole Slide Images.

IEEE journal of biomedical and health informatics
In the domain of histopathology analysis, existing representation learning methods for biomarkers prediction from whole slide images (WSIs) face challenges due to the complexity of tissue subtypes and label noise problems. This paper proposed a novel...

FDDSeg: Unleashing the Power of Scribble Annotation for Cardiac MRI Images Through Feature Decomposition Distillation.

IEEE journal of biomedical and health informatics
Cardiovascular diseases can be diagnosed with computer assistance when using the magnetic resonance imaging (MRI) image that is produced by the MRI sensor. Deep learning-based scribbling MRI image segmentation has demonstrated impressive results rece...

Predicting Blood Pressures for Pregnant Women by PPG and Personalized Deep Learning.

IEEE journal of biomedical and health informatics
Blood pressure (BP) is predicted by this effort based on photoplethysmography (PPG) data to provide effective pre-warning of possible preeclampsia of pregnant women. Towards frequent BP measurement, a PPG sensor device is utilized in this study as a ...

A Fusion Network With Stacked Denoise Autoencoder and Meta Learning for Lateral Walking Gait Phase Recognition and Multi-Step-Ahead Prediction.

IEEE journal of biomedical and health informatics
Lateral walking gait phase recognition and prediction are the premise of hip exoskeleton application in lateral resistance walk exercise. We presented a fusion network with stacked denoise autoencoder and meta learning (SDA-NN-ML) to recognize gait p...

Deep Drug Synergy Prediction Network Using Modified Triangular Mutation-Based Differential Evolution.

IEEE journal of biomedical and health informatics
Drug combination therapy is crucial in cancer treatment, but accurately predicting drug synergy remains a challenge due to the complexity of drug combinations. Machine learning and deep learning models have shown promise in drug combination predictio...

DPFNet: Fast Reconstruction of Multi-Coil MRI Based on Dual Domain Parallel Fusion Network.

IEEE journal of biomedical and health informatics
There are relatively few studies on the multi-coil reconstruction task of existing Magnetic Resonance Imaging (MRI) methods, as there are problems with insufficient reconstruction details, high memory occupation during training, etc. Therefore, a new...

MLVICX: Multi-Level Variance-Covariance Exploration for Chest X-Ray Self-Supervised Representation Learning.

IEEE journal of biomedical and health informatics
Self-supervised learning (SSL) reduces the need for manual annotation in deep learning models for medical image analysis. By learning the representations from unablelled data, self-supervised models perform well on tasks that require little to no fin...

DS-MS-TCN: Otago Exercises Recognition With a Dual-Scale Multi-Stage Temporal Convolutional Network.

IEEE journal of biomedical and health informatics
The Otago Exercise Program (OEP) represents a crucial rehabilitation initiative tailored for older adults, aimed at enhancing balance and strength. Despite previous efforts utilizing wearable sensors for OEP recognition, existing studies have exhibit...

CAGCL: Predicting Short- and Long-Term Breast Cancer Survival With Cross-Modal Attention and Graph Contrastive Learning.

IEEE journal of biomedical and health informatics
In breast cancer treatment, accurately predicting how long a patient will survive is crucial for decision-making. This information guides treatment choices and supports patients' psychological recovery. To address this challenge, we introduce a novel...

Multi-Task Learning for Audio-Based Infant Cry Detection and Reasoning.

IEEE journal of biomedical and health informatics
Infant cry is a crucial indicator that offers valuable insights into their physical and mental conditions, such as hunger and pain. However, the scarcity of infant cry datasets hinders the model's generalization in real-life scenarios. The varying vo...