AIMC Topic: Deep Learning

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Enhancing liver tumor segmentation with UNet-ResNet: Leveraging ResNet's power.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Liver cancer poses a significant health challenge due to its high incidence rates and complexities in detection and treatment. Accurate segmentation of liver tumors using medical imaging plays a crucial role in early diagnosis and treatme...

Automatic anal sphincter integrity detection from ultrasound images via convolutional neural networks.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The anal sphincter complex comprises the anal sphincter and the U-shaped deep and superficial puborectalis muscle. As an important supporting structure of the posterior pelvic floor, together with its surrounding tissues and muscles, the ...

Can temporomandibular joint osteoarthritis be diagnosed on MRI proton density-weighted images with diagnostic support from the latest deep learning classification models?

Dento maxillo facial radiology
OBJECTIVES: This study aimed to clarify the performance of MRI-based deep learning classification models in diagnosing temporomandibular joint osteoarthritis (TMJ-OA) and to compare the developed diagnostic assistance with human observers.

3D DenseNet with temporal transition layer for heart rate estimation from real-life RGB videos.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Deep learning has demonstrated superior performance over traditional methods for the estimation of heart rates in controlled contexts. However, in less controlled scenarios this performance seems to vary based on the training dataset and ...

A Comprehensive Review on Deep Learning Techniques in Alzheimer's Disease Diagnosis.

Current topics in medicinal chemistry
Alzheimer's Disease (AD) is a serious neurological illness that causes memory loss gradually by destroying brain cells. This deadly brain illness primarily strikes the elderly, impairing their cognitive and bodily abilities until brain shrinkage occu...

Exploring the Mechanisms of Sanguinarine in the Treatment of Osteoporosis by Integrating Network Pharmacology Analysis and Deep Learning Technology.

Current computer-aided drug design
BACKGROUND: Sanguinarine (SAN) has been reported to have antioxidant, antiinflammatory, and antimicrobial activities with potential for the treatment of osteoporosis (OP).

Detection of Brain Tumor Employing Residual Network-based Optimized Deep Learning.

Current computer-aided drug design
BACKGROUND: Diagnosis and treatment planning play a very vital role in improving the survival of oncological patients. However, there is high variability in the shape, size, and structure of the tumor, making automatic segmentation difficult. The aut...

Artificial intelligence model for perigastric blood vessel recognition during laparoscopic radical gastrectomy with D2 lymphadenectomy in locally advanced gastric cancer.

BJS open
BACKGROUND: Radical gastrectomy with D2 lymphadenectomy is standard surgical protocol for locally advanced gastric cancer. The surgical experience and skill in recognizing blood vessels and performing lymph node dissection differ between surgeons, wh...

Diagnostic Performance of Deep Learning Applications in Hepatocellular Carcinoma Detection Using Computed Tomography Imaging.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
Hepatocellular carcinoma (HCC) is a prevalent cancer that significantly contributes to mortality globally, primarily due to its late diagnosis. Early detection is crucial yet challenging. This study leverages the potential of deep learning (DL) techn...

Image detection method for multi-category lesions in wireless capsule endoscopy based on deep learning models.

World journal of gastroenterology
BACKGROUND: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has been propelled by advancements in medical imaging technology. However, the complexity of the digestive ...