AIMC Topic: Humans

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Application of ChatGPT in Routine Diagnostic Pathology: Promises, Pitfalls, and Potential Future Directions.

Advances in anatomic pathology
Large Language Models are forms of artificial intelligence that use deep learning algorithms to decipher large amounts of text and exhibit strong capabilities like question answering and translation. Recently, an influx of Large Language Models has e...

Survey shows all surgical residents have exposure to robotic surgery yet no formalized curricula exist amongst programs: A Southwest Surgical Congress Survey.

American journal of surgery
BACKGROUND: Increased robotic surgery exposure during general surgery training occurs at many institutions without a formal education curriculum. Our study evaluates the current state of general surgery robotic training within programs represented by...

Effectiveness of deep learning reconstruction on standard to ultra-low-dose high-definition chest CT images.

Japanese journal of radiology
PURPOSE: Deep learning reconstruction (DLR) has been introduced by major vendors, tested for CT examinations of a variety of organs, and compared with other reconstruction methods. The purpose of this study was to compare the capabilities of DLR for ...

Deep learning-based reconstruction for acceleration of lumbar spine MRI: a prospective comparison with standard MRI.

European radiology
OBJECTIVE: To compare the image quality and diagnostic performance between standard turbo spin-echo MRI and accelerated MRI with deep learning (DL)-based image reconstruction for degenerative lumbar spine diseases.

Automatic prediction of hepatic arterial infusion chemotherapy response in advanced hepatocellular carcinoma with deep learning radiomic nomogram.

European radiology
OBJECTIVES: Hepatic arterial infusion chemotherapy (HAIC) using the FOLFOX regimen (oxaliplatin plus fluorouracil and leucovorin) is a promising option for advanced hepatocellular carcinoma (Ad-HCC). As identifying patients with Ad-HCC who would obta...

Ultrafast review of ambulatory EEGs with deep learning.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: Interictal epileptiform discharges (IED) are hallmark biomarkers of epilepsy which are typically detected through visual analysis. Deep learning has shown potential in automating IED detection, which could reduce the burden of visual analy...

The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors.

Future oncology (London, England)
The RAISE project assessed whether deep learning could improve early progression-free survival (PFS) prediction in patients with neuroendocrine tumors. Deep learning models extracted features from CT scans from patients in CLARINET (NCT00353496) (n...

Association of retinal microvascular density and complexity with incident coronary heart disease.

Atherosclerosis
BACKGROUND AND AIMS: The high mortality rate and huge disease burden of coronary heart disease (CHD) highlight the importance of its early detection and timely intervention. Given the non-invasive nature of fundus photography and recent development i...