AIMC Topic: Deep Learning

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Neural gradient boosting in federated learning for hemodynamic instability prediction: towards a distributed and scalable deep learning-based solution.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Federated learning (FL) is a privacy preserving approach to learning that overcome issues related to data access, privacy, and security, which represent key challenges in the healthcare sector. FL enables hospitals to collaboratively learn a shared p...

Separating Daily 1 km PM Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data.

Environmental science & technology
Fine particulate matter (PM) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model si...

Progressive growing of Generative Adversarial Networks for improving data augmentation and skin cancer diagnosis.

Artificial intelligence in medicine
Early melanoma diagnosis is the most important factor in the treatment of skin cancer and can effectively reduce mortality rates. Recently, Generative Adversarial Networks have been used to augment data, prevent overfitting and improve the diagnostic...

From modern CNNs to vision transformers: Assessing the performance, robustness, and classification strategies of deep learning models in histopathology.

Medical image analysis
While machine learning is currently transforming the field of histopathology, the domain lacks a comprehensive evaluation of state-of-the-art models based on essential but complementary quality requirements beyond a mere classification accuracy. In o...

Real-Time Automatic Assisted Detection of Uterine Fibroid in Ultrasound Images Using a Deep Learning Detector.

Ultrasound in medicine & biology
OBJECTIVE: Uterine smooth muscle hyperplasia causes a tumor called a uterine fibroid. With an incidence of up to 30%, it is one of the most prevalent tumors in women and has the third highest prevalence of all gynecological illnesses. Although uterin...

Efficient Generation of Paired Single-Cell Multiomics Profiles by Deep Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Recent advances in single-cell sequencing technology have made it possible to measure multiple paired omics simultaneously in a single cell such as cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) and single-nucleus chromatin...

An approach for goose egg recognition for robot picking based on deep learning.

British poultry science
1. In a non-cage environment, goose eggs are buried in litter and goose feathers, leading to contamination and discolouration. Such random distribution of goose eggs poses a great challenge to the recognition and location for intelligent picking by r...

A Deep Learning Framework for Processing and Classification of Hyperspectral Rice Seed Images Grown under High Day and Night Temperatures.

Sensors (Basel, Switzerland)
A framework combining two powerful tools of hyperspectral imaging and deep learning for the processing and classification of hyperspectral images (HSI) of rice seeds is presented. A seed-based approach that trains a three-dimensional convolutional ne...

Deep learning-based image enhancement in optical coherence tomography by exploiting interference fringe.

Communications biology
Optical coherence tomography (OCT), an interferometric imaging technique, provides non-invasive, high-speed, high-sensitive volumetric biological imaging in vivo. However, systemic features inherent in the basic operating principle of OCT limit its i...

Preliminary evaluation of deep learning for first-line diagnostic prediction of tumor mutational status.

Scientific reports
The detection of tumour gene mutations by DNA or RNA sequencing is crucial for the prescription of effective targeted therapies. Recent developments showed promising results for tumoral mutational status prediction using new deep learning based metho...