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Found 11 papers, 9 papers with code
Improving Acne Image Grading with Label Distribution Smoothing
Addressing these limitations, we proposed to incorporate severity scale information into lesion counting by combining LDL with label smoothing, and to decouple if from global assessment.
Reproducible image-based profiling with Pycytominer
Technological advances in high-throughput microscopy have facilitated the acquisition of cell images at a rapid pace, and data pipelines can now extract and process thousands of image-based features from microscopy images.
Ten Quick Tips for Deep Learning in Biology
In particular, machine learning is concerned with the development and applications of algorithms that can recognize patterns in data and use them for predictive modeling.
3D Convolutional Neural Networks for Stalled Brain Capillary Detection
Recent advances in imaging technology enabled generation of high-quality 3D images that can be used to visualize stalled blood vessels.
Deep Learning for Automatic Pneumonia Detection
Pneumonia is the leading cause of death among young children and one of the top mortality causes worldwide.
Breast Tumor Cellularity Assessment using Deep Neural Networks
Breast cancer is one of the main causes of death worldwide.
Albumentations: fast and flexible image augmentations
We provide examples of image augmentations for different computer vision tasks and show that Albumentations is faster than other commonly used image augmentation tools on the most of commonly used image transformations.
Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks
Accurate detection and localization for angiodysplasia lesions is an important problem in early stage diagnostics of gastrointestinal bleeding and anemia.
Automatic Instrument Segmentation in Robot-Assisted Surgery Using Deep Learning
Semantic segmentation of robotic instruments is an important problem for the robot-assisted surgery.
Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
In this work, we develop the computational approach based on deep convolution neural networks for breast cancer histology image classification.
Deep Learning in Pharmacogenomics: From Gene Regulation to Patient Stratification
This Perspective provides examples of current and future applications of deep learning in pharmacogenomics, including: (1) identification of novel regulatory variants located in noncoding domains and their function as applied to pharmacoepigenomics; (2) patient stratification from medical records; and (3) prediction of drugs, targets, and their interactions.
