AIMC Topic: Deep Learning

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Towards automated recipe genre classification using semi-supervised learning.

PloS one
Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In...

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...

A Deep Learning Tool for Minimum Joint Space Width Calculation on Antero-posterior Knee Radiographs.

The Journal of arthroplasty
BACKGROUND: Minimum joint space width (mJSW) is an important continuous quantitative metric of osteoarthritis progression in the knee. The purpose of this study was to develop an automated measurement algorithm for mJSW in the medial and lateral comp...

Development of a Deep Learning Model for Automating Implant Position in Total Hip Arthroplasty.

The Journal of arthroplasty
BACKGROUND: Novel methods for annotating antero-posterior pelvis radiographs and fluoroscopic images with deep-learning models have recently been developed. However, their clinical use has been limited. Therefore, the purpose of this study was to dev...

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...