AIMC Topic: Deep Learning

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Parkinson's Disease Recognition Using Decorrelated Convolutional Neural Networks: Addressing Imbalance and Scanner Bias in rs-fMRI Data.

Biosensors
Parkinson's disease (PD) is a neurodegenerative and progressive disease that impacts the nerve cells in the brain and varies from person to person. The exact cause of PD is still unknown, and the diagnosis of PD does not include a specific objective ...

A deep learning approach to explore the association of age-related macular degeneration polygenic risk score with retinal optical coherence tomography: A preliminary study.

Acta ophthalmologica
PURPOSE: Age-related macular degeneration (AMD) is a complex eye disorder affecting millions worldwide. This article uses deep learning techniques to investigate the relationship between AMD, genetics and optical coherence tomography (OCT) scans.

Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Deep learning can automate delineation in radiation therapy, reducing time and variability. Yet, its efficacy varies across different institutions, scanners, or settings, emphasizing the need for adaptable and robust models in clinical envir...

Machine learning, deep learning and hernia surgery. Are we pushing the limits of abdominal core health? A qualitative systematic review.

Hernia : the journal of hernias and abdominal wall surgery
INTRODUCTION: This systematic review aims to evaluate the use of machine learning and artificial intelligence in hernia surgery.

Intrinsically explainable deep learning architecture for semantic segmentation of histological structures in heart tissue.

Computers in biology and medicine
BACKGROUND: Analysis of structures contained in tissue samples and the relevant contextual information is of utmost importance to histopathologists during diagnosis. Cardiac biopsies require in-depth analysis of the relationships between biological s...

Radiomics and deep learning models for CT pre-operative lymph node staging in pancreatic ductal adenocarcinoma: A systematic review and meta-analysis.

European journal of radiology
PURPOSE: To evaluate the diagnostic accuracy of computed tomography (CT)-based radiomic algorithms and deep learning models to preoperatively identify lymph node metastasis (LNM) in patients with pancreatic ductal adenocarcinoma (PDAC).

Artificial intelligence for gastric cancer in endoscopy: From diagnostic reasoning to market.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
Recognition of gastric conditions during endoscopy exams, including gastric cancer, usually requires specialized training and a long learning curve. Besides that, the interobserver variability is frequently high due to the different morphological cha...

Longitudinal artificial intelligence-based deep learning models for diagnosis and prediction of the future occurrence of polyneuropathy in diabetes and prediabetes.

Neurophysiologie clinique = Clinical neurophysiology
OBJECTIVE: The objective of this study was to develop artificial intelligence-based deep learning models and assess their potential utility and accuracy in diagnosing and predicting the future occurrence of diabetic distal sensorimotor polyneuropathy...

Histopathologic image-based deep learning classifier for predicting platinum-based treatment responses in high-grade serous ovarian cancer.

Nature communications
Platinum-based chemotherapy is the cornerstone treatment for female high-grade serous ovarian carcinoma (HGSOC), but choosing an appropriate treatment for patients hinges on their responsiveness to it. Currently, no available biomarkers can promptly ...

Evaluation method for ecology-agriculture-urban spaces based on deep learning.

Scientific reports
With the increasing global population and escalating ecological and farmland degradation, challenges to the environment and livelihoods have become prominent. Coordinating urban development, food security, and ecological conservation is crucial for f...