AIMC Topic: Humans

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Effects of deep learning on radiologists' and radiology residents' performance in identifying esophageal cancer on CT.

The British journal of radiology
OBJECTIVE: To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images.

Cerebrovascular super-resolution 4D Flow MRI - Sequential combination of resolution enhancement by deep learning and physics-informed image processing to non-invasively quantify intracranial velocity, flow, and relative pressure.

Medical image analysis
The development of cerebrovascular disease is tightly coupled to regional changes in intracranial flow and relative pressure. Image-based assessment using phase contrast magnetic resonance imaging has particular promise for non-invasive full-field ma...

Demystifying evidential Dempster Shafer-based CNN architecture for fetal plane detection from 2D ultrasound images leveraging fuzzy-contrast enhancement and explainable AI.

Ultrasonics
Ultrasound imaging is a valuable tool for assessing the development of the fetal during pregnancy. However, interpreting ultrasound images manually can be time-consuming and subject to variability. Automated image categorization using machine learnin...

Artificial Intelligence Applications in Hepatology.

Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Over the past 2 decades, the field of hepatology has witnessed major developments in diagnostic tools, prognostic models, and treatment options making it one of the most complex medical subspecialties. Through artificial intelligence (AI) and machine...

Deep Learning Approaches for Glioblastoma Prognosis in Resource-Limited Settings: A Study Using Basic Patient Demographic, Clinical, and Surgical Inputs.

World neurosurgery
BACKGROUND: Glioblastoma (GBM) is the most common brain tumor in the United States, with an annual incidence rate of 3.21 per 100,000. It is the most aggressive type of diffuse glioma and has a median survival of months after treatment. This study ai...

Digital by design approach to develop a universal deep learning AI architecture for automatic chromatographic peak integration.

Biotechnology and bioengineering
Chromatographic data processing has garnered attention due to multiple Food and Drug Administration 483 citations and warning letters, highlighting the need for a robust technological solution. The healthcare industry has the potential to greatly ben...

A deep learning-based reconstruction approach for accelerated magnetic resonance image of the knee with compressed sense: evaluation in healthy volunteers.

The British journal of radiology
OBJECTIVES: To evaluate the feasibility of combining compressed sense (CS) with a newly developed deep learning-based algorithm (CS-AI) using convolutional neural networks to accelerate 2D MRI of the knee.

Simultaneous Inguinal Hernia Repair with Monofilament Polypropylene Mesh during Robot-Assisted Radical Prostatectomy: Results from a Single Institute Series.

Medicina (Kaunas, Lithuania)
: Inguinal hernia (IH) is a usual finding in men with prostate cancer (PCa) due to their similar risk factors, such as age, gender, and smoking. This study aims to present a single institution's experience with simultaneous IH repair (IHR) and roboti...

Revolutionizing the Early Detection of Alzheimer's Disease through Non-Invasive Biomarkers: The Role of Artificial Intelligence and Deep Learning.

Sensors (Basel, Switzerland)
Alzheimer's disease (AD) is now classified as a silent pandemic due to concerning current statistics and future predictions. Despite this, no effective treatment or accurate diagnosis currently exists. The negative impacts of invasive techniques and ...

Robot-assisted percutaneous balloon compression for trigeminal neuralgia- preliminary experiences.

BMC neurology
OBJECTIVES: This study aims to discuss the availability of robot-assisted percutaneous balloon compression (PBC) for trigeminal neuralgia (TN) and share our preliminary experiences.