AIMC Topic: Deep Learning

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Deep-learning based automated pancreas segmentation on CT scans of chronic pancreatitis patients.

European journal of radiology
OBJECTIVES: This study aimed to develop an artificial intelligence (AI)-based segmentation model for accurate delineation of the complex pancreas in patients with chronic pancreatitis (CP) using computer tomography (CT) scans obtained during routine ...

Deep learning techniques for automated coronary artery segmentation and coronary artery disease detection: A systematic review of the last decade (2013-2024).

Computer methods and programs in biomedicine
BACKGROUND: Coronary artery disease (CAD) is the most common cardiovascular disease, exacting high morbidity and mortality worldwide. CAD is detected on coronary artery imaging; coronary artery segmentation (CAS) of the images is essential for corona...

Comparison of clinical, radiomics, deep learning, and fusion models for predicting early recurrence in locally advanced rectal cancer based on multiparametric MRI: a multicenter study.

European journal of radiology
OBJECTIVE: Predicting early recurrence (ER) in locally advanced rectal cancer (LARC) is critical for clinical decision-making. This study aimed at comparing clinical, deep learning (DL), radiomics, and two fusion models for ER prediction based on mul...

Deep learning models link local cellular features with whole-animal growth dynamics in zebrafish.

Life science alliance
Animal growth is driven by the collective actions of cells, which are reciprocally influenced in real-time by the animal's overall growth state. Whereas cell behavior and animal growth state are expected to be tightly coupled, it is not yet determine...

Discovery of novel potential 11β-HSD1 inhibitors through combining deep learning, molecular modeling, and bio-evaluation.

Molecular diversity
11β-Hydroxysteroid dehydrogenase type 1 (11β-HSD1) has been shown to play an important role in the treatment of impaired glucose tolerance, insulin resistance, dyslipidemia, and obesity and is a promising drug target. In this study, we built a gated ...

Fully automated evaluation of condylar remodeling after orthognathic surgery in skeletal class II patients using deep learning and landmarks.

Journal of dentistry
OBJECTIVE: Condylar remodeling is a key prognostic indicator in maxillofacial surgery for skeletal class II patients. This study aimed to develop and validate a fully automated method leveraging landmark-guided segmentation and registration for effic...

Portable Ultrasound Bladder Volume Measurement Over Entire Volume Range Using a Deep Learning Artificial Intelligence Model in a Selected Cohort: A Proof of Principle Study.

Neurourology and urodynamics
OBJECTIVE: We aimed to prospectively investigate whether bladder volume measured using deep learning artificial intelligence (AI) algorithms (AI-BV) is more accurate than that measured using conventional methods (C-BV) if using a portable ultrasound ...

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing diabetic nephropathy. The early identification of individuals at heightened risk of such complications or their exacerbation can be crucial to set a co...