AIMC Topic: Deep Learning

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Integrating AI/ML and multi-omics approaches to investigate the role of TNFRSF10A/TRAILR1 and its potential targets in pancreatic cancer.

Computers in biology and medicine
Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, with a five-year survival of under 10 % despite current therapies. Aggressive tumor biology, a desmoplastic stroma that limits drug delivery and immune cell infiltra...

Modeling enteric methane emission from dairy cows using deep learning approach.

The Science of the total environment
This study explores the application of deep learning (DL) models to predict methane (CH) emissions from enteric fermentation in dairy cows using performance, feeding, behavioral and weather data from automated milking and feeding systems, behavioral ...

Deep learning-based histopathologic segmentation of peritubular capillaries in kidney transplant biopsies.

Computers in biology and medicine
BACKGROUND: Assessing the extent of inflammation in peritubular capillaries (PTCs) is important for diagnosing antibody-mediated rejection in kidney transplant biopsies. However, this assessment is time-consuming and suffers from interobserver variab...

Comparison of three classifiers in detection of obstruction of the lower urinary tract using recorded sounds of voiding.

Computers in biology and medicine
The aim of this research is to help health care professionals to automatically detect lower urinary tract disorders using sounds of voiding recorded at home. In total 93 patients were diagnosed as obstructed or non-obstructed in a hospital using trad...

A general survey on medical image super-resolution via deep learning.

Computers in biology and medicine
Medical image super-resolution (SR) is a classic regression task in low-level vision. Limited by hardware limitations, acquisition time, low radiation dose, and other factors, the spatial resolution of some medical images is not sufficient. To addres...

Meta-analysis of AI-based pulmonary embolism detection: How reliable are deep learning models?

Computers in biology and medicine
RATIONALE AND OBJECTIVES: Deep learning (DL)-based methods show promise in detecting pulmonary embolism (PE) on CT pulmonary angiography (CTPA), potentially improving diagnostic accuracy and workflow efficiency. This meta-analysis aimed to (1) determ...

Prostate cancer prediction through a hybrid deep learning method applied to histopathological image.

Expert review of anticancer therapy
BACKGROUND: Prostate Cancer (PCa) is a severe disease that affects males globally. The Gleason grading system is a widely recognized method for diagnosing the aggressiveness of PCa using histopathological images. This system evaluates prostate tissue...

Unraveling the neural dynamics of mathematical interference in english reading: A novel approach with deep learning and fNIRS data.

Brain research bulletin
English has emerged as the predominant global language, driving efforts to optimize its acquisition through interdisciplinary cognitive research. While behavioral studies suggest a link between English learning and mathematical cognition, the neural ...

A multimodal deep learning framework for enzyme turnover prediction with missing modality.

Computers in biology and medicine
Accurate prediction of the turnover number (k), which quantifies the maximum rate of substrate conversion at an enzyme's active site, is essential for assessing catalytic efficiency and understanding biochemical reaction mechanisms. Traditional wet-l...