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Deep learning-based 3D brain multimodal medical image registration
Medical image registration is a critical preprocessing step in medical image analysis. While traditional medical image registration techniques have...
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Predicting long-term progression of Alzheimer’s disease using a multimodal deep learning model incorporating interaction effects
BackgroundIdentifying individuals with mild cognitive impairment (MCI) at risk of progressing to Alzheimer’s disease (AD) provides a unique...
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Prediction of recurrence risk in endometrial cancer with multimodal deep learning
Predicting distant recurrence of endometrial cancer (EC) is crucial for personalized adjuvant treatment. The current gold standard of combined...
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DeepGAMI: deep biologically guided auxiliary learning for multimodal integration and imputation to improve genotype–phenotype prediction
BackgroundGenotypes are strongly associated with disease phenotypes, particularly in brain disorders. However, the molecular and cellular mechanisms...
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Explainable Deep-Learning-Based Diagnosis of Alzheimer’s Disease Using Multimodal Input Fusion of PET and MRI Images
PurposeAlzheimer’s disease (AD) is a progressive, incurable human brain illness that impairs reasoning and retention as well as recall. Detecting AD...
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A transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
During the diagnostic process, clinicians leverage multimodal information, such as the chief complaint, medical images and laboratory test results....
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Machine learning with multimodal neuroimaging data to classify stages of Alzheimer’s disease: a systematic review and meta-analysis
In recent years, Alzheimer’s disease (AD) has been a serious threat to human health. Researchers and clinicians alike encounter a significant...
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Harnessing deep learning for population genetic inference
In population genetics, the emergence of large-scale genomic data for various species and populations has provided new opportunities to understand...
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Prospective assessment of breast cancer risk from multimodal multiview ultrasound images via clinically applicable deep learning
The clinical application of breast ultrasound for the assessment of cancer risk and of deep learning for the classification of breast-ultrasound...
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Big data and deep learning for RNA biology
The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries....
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A systematic analysis of deep learning in genomics and histopathology for precision oncology
BackgroundDigitized histopathological tissue slides and genomics profiling data are available for many patients with solid tumors. In the last 5...
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Deep learning in cancer genomics and histopathology
Histopathology and genomic profiling are cornerstones of precision oncology and are routinely obtained for patients with cancer. Traditionally,...
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Parotid Gland Segmentation Using Purely Transformer-Based U-Shaped Network and Multimodal MRI
Parotid gland tumors account for approximately 2% to 10% of head and neck tumors. Segmentation of parotid glands and tumors on magnetic resonance...
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Brain-inspired multisensory integration neural network for cross-modal recognition through spatiotemporal dynamics and deep learning
The integration and interaction of cross-modal senses in brain neural networks can facilitate high-level cognitive functionalities. In this work, we...
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Toward metacognition: subject-aware contrastive deep fusion representation learning for EEG analysis
We propose a subject-aware contrastive learning deep fusion neural network framework for effectively classifying subjects’ confidence levels in the...
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PSPN: Pseudo-Siamese Pyramid Network for multimodal emotion analysis
Emotion recognition plays an important role in human life and healthcare. The EEG has been extensively researched as an objective indicator of...
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Automatic Detection of Alzheimer's Disease using Deep Learning Models and Neuro-Imaging: Current Trends and Future Perspectives
Deep learning algorithms have a huge influence on tackling research issues in the field of medical image processing. It acts as a vital aid for the...
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Cervical cell classification with deep-learning algorithms
Cervical cancer is a serious threat to the lives and health of women. The accurate analysis of cervical cell smear images is an important diagnostic...
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BraNet: a mobil application for breast image classification based on deep learning algorithms
Mobile health apps are widely used for breast cancer detection using artificial intelligence algorithms, providing radiologists with second opinions...
