AIMC Topic: Deep Learning

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A Deep Learning Radiomics Analysis for Survival Prediction in Esophageal Cancer.

Journal of healthcare engineering
The purpose of this study was to explore the deep learning radiomics (DLR) nomogram to predict the overall 3-year survival after chemoradiotherapy in patients with esophageal cancer. The 154 patients' data were used in this study, which was randomly ...

Development and validation of a deep learning model for detection of breast cancers in mammography from multi-institutional datasets.

PloS one
OBJECTIVES: The objective of this study was to develop and validate a state-of-the-art, deep learning (DL)-based model for detecting breast cancers on mammography.

Bridging the gap between GRACE and GRACE-FO missions with deep learning aided water storage simulations.

The Science of the total environment
The monthly high-resolution terrestrial water storage anomalies (TWSA) during the 11-months of gap between GRACE (Gravity Recovery And Climate Experiment) and its successor GRACE-FO (-Follow On) missions are missing. The continuity of the GRACE-like ...

A fully automated sex estimation for proximal femur X-ray images through deep learning detection and classification.

Legal medicine (Tokyo, Japan)
PURPOSE: To develop a fully automated deep learning pipeline using digital radiographs to detect the proximal femur region for accurate automated sex estimation.

Medical image diagnosis of prostate tumor based on PSP-Net+VGG16 deep learning network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Prostate cancer is the most common cancer of the male reproductive system. With the development of medical imaging technology, magnetic resonance images (MRI) have been used in the diagnosis and treatment of prostate cancer ...

A ensemble methodology for automatic classification of chest X-rays using deep learning.

Computers in biology and medicine
Chest radiographies, or chest X-rays, are the most standard imaging exams used in daily hospitals. Responsible for assisting in detecting numerous pathologies and findings that directly interfere in the patient's life, this exam is therefore crucial ...

Toward Totally Defined Nanocatalysis: Deep Learning Reveals the Extraordinary Activity of Single Pd/C Particles.

Journal of the American Chemical Society
Homogeneous catalysis is typically considered "well-defined" from the standpoint of catalyst structure unambiguity. In contrast, heterogeneous nanocatalysis often falls into the realm of "poorly defined" systems. Supported catalysts are difficult to ...

Mitigating spread of contamination in meat supply chain management using deep learning.

Scientific reports
Industry 4.0 recommends a paradigm shift from traditional manufacturing to automated industrial practices, especially in different parts of supply chain management. Besides, the Sustainable Development Goal (SDG) 12 underscores the urgency of ensurin...

Deep learning model can improve the diagnosis rate of endoscopic chronic atrophic gastritis: a prospective cohort study.

BMC gastroenterology
BACKGROUND AND AIMS: Chronic atrophic gastritis (CAG) is a precancerous form of gastric cancer. However, with pathological diagnosis as the gold standard, the sensitivity of endoscopic diagnosis of atrophy is only 42%. We developed a deep learning (D...

Causal discovery of drivers of surface ozone variability in Antarctica using a deep learning algorithm.

Environmental science. Processes & impacts
The discovery of causal structures behind a phenomenon under investigation has been at the heart of scientific inquiry since the beginning. Randomized control trials, the gold standard for causal analysis, may not always be feasible, such as in the d...