AIMC Topic: Deep Learning

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A novel staging system based on deep learning for overall survival in patients with esophageal squamous cell carcinoma.

Journal of cancer research and clinical oncology
PURPOSE: We developed DeepSurv, a deep learning approach for predicting overall survival (OS) in patients with esophageal squamous cell carcinoma (ESCC). We validated and visualized the novel staging system based on DeepSurv using data from multiple ...

FiNuTyper: Design and validation of an automated deep learning-based platform for simultaneous fiber and nucleus type analysis in human skeletal muscle.

Acta physiologica (Oxford, England)
AIM: While manual quantification is still considered the gold standard for skeletal muscle histological analysis, it is time-consuming and prone to investigator bias. To address this challenge, we assembled an automated image analysis pipeline, FiNuT...

Discrimination Between Glioblastoma and Solitary Brain Metastasis Using Conventional MRI and Diffusion-Weighted Imaging Based on a Deep Learning Algorithm.

Journal of digital imaging
This study aims to develop and validate a deep learning (DL) model to differentiate glioblastoma from single brain metastasis (BM) using conventional MRI combined with diffusion-weighted imaging (DWI). Preoperative conventional MRI and DWI of 202 pat...

Deep learning referral suggestion and tumour discrimination using explainable artificial intelligence applied to multiparametric MRI.

European radiology
OBJECTIVES: An appropriate and fast clinical referral suggestion is important for intra-axial mass-like lesions (IMLLs) in the emergency setting. We aimed to apply an interpretable deep learning (DL) system to multiparametric MRI to obtain clinical r...

Machine and deep learning in inflammatory bowel disease.

Current opinion in gastroenterology
PURPOSE OF REVIEW: The Management of inflammatory bowel disease (IBD) has evolved with the introduction and widespread adoption of biologic agents; however, the advent of artificial intelligence technologies like machine learning and deep learning pr...

Deep learning to refine the identification of high-quality clinical research articles from the biomedical literature: Performance evaluation.

Journal of biomedical informatics
BACKGROUND: Identifying practice-ready evidence-based journal articles in medicine is a challenge due to the sheer volume of biomedical research publications. Newer approaches to support evidence discovery apply deep learning techniques to improve th...

Gender-specific data-driven adiposity subtypes using deep-learning-based abdominal CT segmentation.

Obesity (Silver Spring, Md.)
OBJECTIVE: The aim of this study was to quantify abdominal adiposity and generate data-driven adiposity subtypes with different diabetes risks.

EmbryoNet: using deep learning to link embryonic phenotypes to signaling pathways.

Nature methods
Evolutionarily conserved signaling pathways are essential for early embryogenesis, and reducing or abolishing their activity leads to characteristic developmental defects. Classification of phenotypic defects can identify the underlying signaling mec...

An Investigation about Modern Deep Learning Strategies for Colon Carcinoma Grading.

Sensors (Basel, Switzerland)
Developing computer-aided approaches for cancer diagnosis and grading is currently receiving an increasing demand: this could take over intra- and inter-observer inconsistency, speed up the screening process, increase early diagnosis, and improve the...

Automatic detection and recognition of nasopharynx gross tumour volume (GTVnx) by deep learning for nasopharyngeal cancer radiotherapy through magnetic resonance imaging.

Radiation oncology (London, England)
BACKGROUND: In this study, we propose the deep learning model-based framework to automatically delineate nasopharynx gross tumor volume (GTVnx) in MRI images.