AIMC Topic: Deep Learning

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A Survey of Few-Shot Learning for Biomedical Time Series.

IEEE reviews in biomedical engineering
Advancements in wearable sensor technologies and the digitization of medical records have contributed to the unprecedented ubiquity of biomedical time series data. Data-driven models have tremendous potential to assist clinical diagnosis and improve ...

Data- and Physics-Driven Deep Learning Based Reconstruction for Fast MRI: Fundamentals and Methodologies.

IEEE reviews in biomedical engineering
Magnetic Resonance Imaging (MRI) is a pivotal clinical diagnostic tool, yet its extended scanning times often compromise patient comfort and image quality, especially in volumetric, temporal and quantitative scans. This review elucidates recent advan...

Deep Learning in Breast Cancer Imaging: A Decade of Progress and Future Directions.

IEEE reviews in biomedical engineering
Breast cancer has reached the highest incidence rate worldwide among all malignancies since 2020. Breast imaging plays a significant role in early diagnosis and intervention to improve the outcome of breast cancer patients. In the past decade, deep l...

Identifying Primary Sites of Spinal Metastases: Expert-Derived Features vs. ResNet50 Model Using Nonenhanced MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: The spinal column is a frequent site for metastases, affecting over 30% of solid tumor patients. Identifying the primary tumor is essential for guiding clinical decisions but often requires resource-intensive diagnostics.

Identification of Gingival Inflammation Surface Image Features Using Intraoral Scanning and Deep Learning.

International dental journal
INTRODUCTION AND AIM: The assessment of gingival inflammation surface features mainly depends on subjective judgment and lacks quantifiable and reproducible indicators. Therefore, it is a need to acquire objective identification information for accur...

Deep one-class probability learning for end-to-end image classification.

Neural networks : the official journal of the International Neural Network Society
One-class learning has many application potentials in novelty, anomaly, and outlier detection systems. It aims to distinguish both positive and negative samples with a model trained via only positive samples or one-class annotated samples. With the d...

A novel clinical investigation using deep learning and human-in-the-loop approach in orbital volume measurement.

Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery
Orbital volume assessment is crucial for surgical planning. Traditional methods lack efficiency and accuracy. Recent studies explore AI-driven techniques, but research on their clinical effectiveness is limited. This study included 349 patients aged ...

Dissecting the effectiveness of deep features as metric of perceptual image quality.

Neural networks : the official journal of the International Neural Network Society
There is an open debate on the role of artificial networks to understand the visual brain. Internal representations of images in artificial networks develop human-like properties. In particular, evaluating distortions using differences between intern...

PSMA PET/CT based multimodal deep learning model for accurate prediction of pelvic lymph-node metastases in prostate cancer patients identified as candidates for extended pelvic lymph node dissection by preoperative nomograms.

European journal of nuclear medicine and molecular imaging
PURPOSE: To develop and validate a prostate-specific membrane antigen (PSMA) PET/CT based multimodal deep learning model for predicting pathological lymph node invasion (LNI) in prostate cancer (PCa) patients identified as candidates for extended pel...